Error : when i try to use fit

Hi.
I tried to use to fit option and ended up with a error. i am not able to interpret the error. Somebody please try to help me out.

data = CSV.read("E:\\dontdelete\\data\\lev3cjul.csv", missingstring = ".")
jd2  =  read_pumas(data, covariates = [:WT], observations = [:DV],  id = :ID, time = :TIME,evid = :EVID, amt = :DOSE,
                  addl = :ADL, ii = :II,  cmt = :CMT, mdv = :MDV, event_data = true)
result  = fit(jef,jd2, param, Pumas.FOCEI())

error is


julia> result  = fit(jef,jd2, param, Pumas.FOCEI())
ERROR: MethodError: no method matching inverse_eltype(::TransformVariables.Identity, ::Array{Float64,1})
Closest candidates are:
  inverse_eltype(::TransformVariables.UnitVector, ::AbstractArray{T,1} where T<:Real) at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\special_arrays.jl:69
  inverse_eltype(::TransformVariables.ScalarTransform, ::T) where T<:Real at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\scalar.jl:26
  inverse_eltype(::TransformVariables.ArrayTransform, ::AbstractArray) at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\aggregation.jl:73
  ...
Stacktrace:
 [1] (::TransformVariables.var"#8#9")(::Tuple{TransformVariables.Identity,Array{Float64,1}}) at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\aggregation.jl:183
 [2] MappingRF at .\reduce.jl:93 [inlined]
 [3] _foldl_impl(::Base.MappingRF{TransformVariables.var"#8#9",Base.BottomRF{typeof(promote_type)}}, ::Base._InitialValue, ::Base.Iterators.Zip{Tuple{Tuple{TransformVariables.ShiftedExp{true,Int64},TransformVariables.ShiftedExp{true,Int64},TransformVariables.ShiftedExp{true,Int64},TransformVariables.Identity,TransformVariables.ShiftedExp{true,Int64}},Tuple{Float64,Float64,Float64,Array{Float64,1},Float64}}}) at .\reduce.jl:62
 [4] foldl_impl at .\reduce.jl:48 [inlined]
 [5] mapfoldl_impl at .\reduce.jl:44 [inlined]
 [6] #mapfoldl#204 at .\reduce.jl:160 [inlined]
 [7] mapfoldl at .\reduce.jl:160 [inlined]
 [8] #mapreduce#208 at .\reduce.jl:287 [inlined]
 [9] mapreduce at .\reduce.jl:287 [inlined]
 [10] _inverse_eltype_tuple at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\aggregation.jl:182 [inlined]
 [11] inverse_eltype at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\aggregation.jl:230 [inlined]
 [12] inverse(::TransformVariables.TransformTuple{NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{TransformVariables.ShiftedExp{true,Int64},TransformVariables.ShiftedExp{true,Int64},TransformVariables.ShiftedExp{true,Int64},TransformVariables.Identity,TransformVariables.ShiftedExp{true,Int64}}}}, ::NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{Float64,Float64,Float64,Array{Float64,1},Float64}}) at C:\Users\julia\.julia\packages\TransformVariables\a4AMY\src\generic.jl:206
 [13] fit(::PumasModel{ParamSet{NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{TransformVariables.Infinity{false},TransformVariables.Infinity{true},Array{Float64,1}},RealDomain{Int64,TransformVariables.Infinity{true},Float64}}}},var"#91#103",var"#92#104",var"#93#105",ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,ODEFunction{false,var"#94#106",LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},var"#95#107",var"#99#111"}, ::Array{Subject{NamedTuple{(:DV,),Tuple{Array{Union{Missing, Float64},1}}},Pumas.ConstantCovar{NamedTuple{(:WT,),Tuple{Int64}}},Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Int64},1},Array{Float64,1}},1}, ::NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{Float64,Float64,Float64,Array{Float64,1},Float64}}, ::Pumas.FOCEI; optimize_fn::Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}}, constantcoef::NamedTuple{,Tuple{}}, omegas::Tuple{}, ensemblealg::EnsembleSerial, checkidentification::Bool, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}}) at C:\Users\julia\.julia\packages\Pumas\Aw4s7\src\estimation\likelihoods.jl:1620
 [14] fit(::PumasModel{ParamSet{NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{Int64,TransformVariables.Infinity{true},Float64},RealDomain{TransformVariables.Infinity{false},TransformVariables.Infinity{true},Array{Float64,1}},RealDomain{Int64,TransformVariables.Infinity{true},Float64}}}},var"#91#103",var"#92#104",var"#93#105",ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,ODEFunction{false,var"#94#106",LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},var"#95#107",var"#99#111"}, ::Array{Subject{NamedTuple{(:DV,),Tuple{Array{Union{Missing, Float64},1}}},Pumas.ConstantCovar{NamedTuple{(:WT,),Tuple{Int64}}},Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Int64},1},Array{Float64,1}},1}, ::NamedTuple{(:tvcl, :tvv, :tvka, :ฮฉ, :ฯƒ),Tuple{Float64,Float64,Float64,Array{Float64,1},Float64}}, ::Pumas.FOCEI) at C:\Users\julia\.julia\packages\Pumas\Aw4s7\src\estimation\likelihoods.jl:1605
 [15] top-level scope at none:1

@sai_matcha can you show the model and the parameters?

From the error my guess is you are passing in a parameter as an array after specifying it as RealDomain in the model. But it would be easier to diagnose if you post the entire script.

jef = @model begin
  @param begin
    tvcl  โˆˆ RealDomain(lower=0,init = 2.10)
    tvv   โˆˆ RealDomain(lower=0,init=20.4)
    tvka  โˆˆ RealDomain(lower=0,init=2.56)
    ฮฉ     โˆˆ RealDomain(init = [0.03,0.72,0.01])
    ฯƒ     โˆˆ RealDomain(lower=0,init=0.03)
  end
  @random begin
    ฮท ~ MvNormal(ฮฉ)
  end

  @covariates WT

  @pre begin
    cl = tvcl * ((WT/32)^0.75) * exp(ฮท[1])
    v  = tvv * (WT/32) * exp(ฮท[2])
    ka = tvka * exp(ฮท[3])
  end
  @dynamics begin
    Depot'  = -ka * Depot
    Central' = ka * Depot - (cl/v) * Central
  end
  @derived begin
    cp = @. Central/v
    dv ~ @. Normal(cp,abs(cp)*ฯƒ)
  end
end

param = init_param(jef)

data = CSV.read("E:\\dontdelete\\data\\lev3cjul.csv", missingstring = ".")
jd2  =  read_pumas(data, covariates = [:WT], observations = [:DV],  id = :ID, time = :TIME,evid = :EVID, amt = :DOSE,
                  addl = :ADL, ii = :II,  cmt = :CMT, mdv = :MDV, event_data = true)

result  = fit(jef,jd2, param, Pumas.FOCEI())

Thank you

Thatโ€™s not correct you would need to make it a PDiagDomain or PSDDomain as mentioned in the docs https://docs.pumas.ai/model_components/domains/#Positive-Definite-Matrix-Domains

1 Like

HI , I have corrected it and run the code to fit . it took long time and gave this error. May i know where i went wrong?

 @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: First function call produced NaNs. Exiting.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\initdt.jl:137
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459

Could you please try to add upper bounds on the parameters?

tried with upper bounds, still got the error.

jef = @model begin
  @param begin
    tvcl  โˆˆ RealDomain(lower=0,init = 2.10, upper = 6.00)
    tvv   โˆˆ RealDomain(lower=0,init=20.4, upper = 60.0)
    tvka  โˆˆ RealDomain(lower=0,init=2.56, upper = 4.00)
    ฮฉ     โˆˆ PDiagDomain(init = [0.03,0.72,0.01])
    ฯƒ     โˆˆ RealDomain(lower=0,init=0.03, upper = 0.09)
  end
  @random begin
    ฮท ~ MvNormal(ฮฉ)
  end

  @covariates WT

  @pre begin
    cl = tvcl * ((WT/32)^0.75) * exp(ฮท[1])
    v  = tvv * (WT/32) * exp(ฮท[2])
    ka = tvka * exp(ฮท[3])
  end
  @dynamics begin
    Depot'  = -ka * Depot
    Central' = ka * Depot - (cl/v) * Central
  end
  @derived begin
    cp = @. Central/v
    DV ~ @. Normal(cp,abs(cp)*ฯƒ)
  end
end

Error

โ”Œ Warning: `CSV.read(input; kw...)` is deprecated in favor of `using DataFrames; CSV.read(input, DataFrame; kw...)
โ”‚   caller = ip:0x0
โ”” @ Core :-1
Iter     Function value   Gradient norm
     0     1.548587e+03     1.268852e+03
 * time: 0.0
     1     8.435076e+02     9.089784e+01
 * time: 167.0659999847412
     2     8.375654e+02     4.042908e+01
 * time: 287.4100000858307
     3     8.348340e+02     3.195578e+01
 * time: 399.74900007247925
     4     8.318014e+02     4.490897e+01
 * time: 507.0550000667572
     5     8.233371e+02     7.519804e+01
 * time: 608.1349999904633
     6     8.140463e+02     5.850264e+01
 * time: 714.5989999771118
     7     8.121861e+02     3.495585e+01
 * time: 814.9479999542236
     8     8.103656e+02     2.165011e+01
 * time: 916.8310000896454
     9     8.090966e+02     1.986339e+01
 * time: 1017.1089999675751
    10     8.082441e+02     2.652343e+01
 * time: 1109.7710001468658
    11     8.038401e+02     4.311920e+01
 * time: 1208.0280001163483
    12     7.992064e+02     3.362408e+01
 * time: 1302.1240000724792
    13     7.951483e+02     1.165965e+01
 * time: 1392.1219999790192
    14     7.940328e+02     2.651264e+00
 * time: 1480.4700000286102
    15     7.933769e+02     6.626426e+00
 * time: 1564.7890000343323
    16     7.927445e+02     4.099096e+00
 * time: 1649.0460000038147
    17     7.922602e+02     2.855701e+00
 * time: 1735.4800000190735
    18     7.920801e+02     8.783436e+00
 * time: 1821.0880000591278
    19     7.919837e+02     8.726402e+00
 * time: 1903.324000120163
    20     7.918311e+02     9.197960e+00
 * time: 1985.7460000514984
    21     7.916380e+02     2.887579e+00
 * time: 2070.776999950409
    22     7.915628e+02     7.248123e+00
 * time: 2155.811000108719
    23     7.914762e+02     2.044749e+00
 * time: 2240.5889999866486
    24     7.913927e+02     1.948018e+00
 * time: 2319.391000032425
    25     7.913300e+02     3.973446e+00
 * time: 2403.138999938965
    26     7.912718e+02     1.423472e+00
 * time: 2486.5080001354218
    27     7.912423e+02     4.181085e+00
 * time: 2570.5789999961853
    28     7.912091e+02     1.258464e+00
 * time: 2654.7269999980927
    29     7.911842e+02     1.064435e+00
 * time: 2730.077000141144
    30     7.911654e+02     7.152543e-01
 * time: 2806.6289999485016
    31     7.911525e+02     6.992937e-01
 * time: 2882.8280000686646
    32     7.911435e+02     2.646921e-01
 * time: 2958.588000059128
    33     7.911389e+02     1.238082e+00
 * time: 3040.4690001010895
    34     7.911330e+02     1.175908e-01
 * time: 3120.888999938965
    35     7.911302e+02     1.159948e-01
 * time: 3193.3840000629425
    36     7.911263e+02     2.096699e-01
 * time: 3265.6019999980927
    37     7.911195e+02     2.142946e-01
 * time: 3335.890000104904
    38     7.910886e+02     9.777066e-02
 * time: 3407.4700000286102
    39     7.910609e+02     1.594389e-01
 * time: 3475.4850001335144
    40     7.910539e+02     1.223305e-01
 * time: 3540.7400000095367
    41     7.910507e+02     6.640475e-02
 * time: 3604.1770000457764
    42     7.910496e+02     3.375386e-02
 * time: 3665.9100000858307
    43     7.910493e+02     1.603955e-02
 * time: 3726.0640001296997
    44     7.910492e+02     6.529235e-03
 * time: 3785.2200000286102
    45     7.910492e+02     6.528111e-03
 * time: 3844.294000148773
    46     7.910492e+02     6.525343e-03
 * time: 3895.7009999752045
    47     7.910492e+02     6.524348e-03
 * time: 3945.0090000629425
    48     7.910492e+02     6.520674e-03
 * time: 3996.6820001602173
    49     7.910492e+02     6.515798e-03
 * time: 4049.305000066757
    50     7.910492e+02     6.506572e-03
 * time: 4105.000999927521
    51     7.910492e+02     7.069872e-03
 * time: 4163.013999938965
    52     7.910492e+02     1.186504e-02
 * time: 4221.548000097275
    53     7.910492e+02     1.933440e-02
 * time: 4278.401000022888
    54     7.910491e+02     3.088907e-02
 * time: 4335.7699999809265
    55     7.910489e+02     4.794689e-02
 * time: 4393.154000043869
    56     7.910485e+02     6.769449e-02
 * time: 4450.960999965668
    57     7.910476e+02     5.501720e-02
 * time: 4511.641000032425
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323
โ”Œ Warning: Automatic dt set the starting dt as NaN, causing instability.
โ”” @ OrdinaryDiffEq C:\Users\julia\.julia\packages\OrdinaryDiffEq\VPJBD\src\solve.jl:459
โ”Œ Warning: NaN dt detected. Likely a NaN value in the state, parameters, or derivative value caused this outcome.
โ”” @ DiffEqBase C:\Users\julia\.julia\packages\DiffEqBase\T7EPc\src\integrator_interface.jl:323

this is how my original data looks like

julia> data
440ร—27 DataFrame. Omitted printing of 6 columns
โ”‚ Row โ”‚ ID    โ”‚ TIME    โ”‚ DOSE  โ”‚ TDOSE โ”‚ ADL   โ”‚ ADDL  โ”‚ II    โ”‚ DV       โ”‚ EVID  โ”‚ MDV   โ”‚ CMT   โ”‚ TAD      โ”‚ TDL     โ”‚ Age   โ”‚ Sex   โ”‚ Height โ”‚ WT    โ”‚ Phenytoin โ”‚ Phenobarbitone โ”‚ Carbamazepine โ”‚ Clobazam โ”‚
โ”‚     โ”‚ Int64 โ”‚ Float64 โ”‚ Int64 โ”‚ Int64 โ”‚ Int64 โ”‚ Int64 โ”‚ Int64 โ”‚ Float64? โ”‚ Int64 โ”‚ Int64 โ”‚ Int64 โ”‚ Float64? โ”‚ Float64 โ”‚ Int64 โ”‚ Int64 โ”‚ Int64  โ”‚ Int64 โ”‚ Int64     โ”‚ Int64          โ”‚ Int64         โ”‚ Float64  โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚ 1   โ”‚ 1     โ”‚ 0.0     โ”‚ 500   โ”‚ 1000  โ”‚ 60    โ”‚ 1440  โ”‚ 12    โ”‚ missing  โ”‚ 1     โ”‚ 1     โ”‚ 1     โ”‚ missing  โ”‚ 1.0     โ”‚ 42    โ”‚ 1     โ”‚ 142    โ”‚ 52    โ”‚ 0         โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ”‚ 2   โ”‚ 1     โ”‚ 732.0   โ”‚ 0     โ”‚ 1000  โ”‚ 0     โ”‚ 1440  โ”‚ 0     โ”‚ 27.76    โ”‚ 0     โ”‚ 0     โ”‚ 2     โ”‚ 12.0     โ”‚ 1.0     โ”‚ 42    โ”‚ 1     โ”‚ 142    โ”‚ 52    โ”‚ 0         โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ”‚ 3   โ”‚ 2     โ”‚ 0.0     โ”‚ 500   โ”‚ 1000  โ”‚ 60    โ”‚ 480   โ”‚ 12    โ”‚ missing  โ”‚ 1     โ”‚ 1     โ”‚ 1     โ”‚ missing  โ”‚ 1.0     โ”‚ 30    โ”‚ 1     โ”‚ 187    โ”‚ 68    โ”‚ 300       โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ”‚ 4   โ”‚ 2     โ”‚ 732.0   โ”‚ 0     โ”‚ 1000  โ”‚ 0     โ”‚ 480   โ”‚ 0     โ”‚ 16.0     โ”‚ 0     โ”‚ 0     โ”‚ 2     โ”‚ 12.0     โ”‚ 1.0     โ”‚ 30    โ”‚ 1     โ”‚ 187    โ”‚ 68    โ”‚ 300       โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ‹ฎ
โ”‚ 436 โ”‚ 247   โ”‚ 734.0   โ”‚ 0     โ”‚ 1500  โ”‚ 0     โ”‚ 720   โ”‚ 0     โ”‚ 2.13     โ”‚ 0     โ”‚ 0     โ”‚ 2     โ”‚ 14.0     โ”‚ 1.0     โ”‚ 55    โ”‚ 2     โ”‚ 154    โ”‚ 48    โ”‚ 300       โ”‚ 0              โ”‚ 200           โ”‚ 0.0      โ”‚
โ”‚ 437 โ”‚ 248   โ”‚ 0.0     โ”‚ 500   โ”‚ 1500  โ”‚ 90    โ”‚ 1440  โ”‚ 8     โ”‚ missing  โ”‚ 1     โ”‚ 1     โ”‚ 1     โ”‚ missing  โ”‚ 1.0     โ”‚ 23    โ”‚ 2     โ”‚ 160    โ”‚ 40    โ”‚ 0         โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ”‚ 438 โ”‚ 248   โ”‚ 733.75  โ”‚ 0     โ”‚ 1500  โ”‚ 0     โ”‚ 1440  โ”‚ 0     โ”‚ 8.9      โ”‚ 0     โ”‚ 0     โ”‚ 2     โ”‚ 13.75    โ”‚ 1.0     โ”‚ 23    โ”‚ 2     โ”‚ 160    โ”‚ 40    โ”‚ 0         โ”‚ 0              โ”‚ 0             โ”‚ 0.0      โ”‚
โ”‚ 439 โ”‚ 249   โ”‚ 0.0     โ”‚ 500   โ”‚ 1500  โ”‚ 90    โ”‚ 4500  โ”‚ 8     โ”‚ missing  โ”‚ 1     โ”‚ 1     โ”‚ 1     โ”‚ missing  โ”‚ 1.0     โ”‚ 37    โ”‚ 1     โ”‚ 175    โ”‚ 55    โ”‚ 0         โ”‚ 300            โ”‚ 0             โ”‚ 30.0     โ”‚
โ”‚ 440 โ”‚ 249   โ”‚ 733.75  โ”‚ 0     โ”‚ 1500  โ”‚ 0     โ”‚ 4500  โ”‚ 0     โ”‚ 4.42     โ”‚ 0     โ”‚ 0     โ”‚ 2     โ”‚ 13.75    โ”‚ 1.0     โ”‚ 37    โ”‚ 1     โ”‚ 175    โ”‚ 55    โ”‚ 0         โ”‚ 300            โ”‚ 0             โ”‚ 30.0     โ”‚

this is how it looks after going through read_pumas

julia> DataFrame(jd2)
14312ร—13 DataFrame
โ”‚ Row   โ”‚ id     โ”‚ time    โ”‚ evid  โ”‚ DV       โ”‚ amt      โ”‚ dose    โ”‚ tad     โ”‚ cmt    โ”‚ ss    โ”‚ ii       โ”‚ base_time โ”‚ rate_dir โ”‚ WT    โ”‚
โ”‚       โ”‚ String โ”‚ Float64 โ”‚ Int64 โ”‚ Float64? โ”‚ Float64? โ”‚ Float64 โ”‚ Float64 โ”‚ Int64? โ”‚ Int64 โ”‚ Float64? โ”‚ Float64?  โ”‚ Int8?    โ”‚ Int64 โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚ 1     โ”‚ 1      โ”‚ 0.0     โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 12.0     โ”‚ 0.0       โ”‚ 1        โ”‚ 52    โ”‚
โ”‚ 2     โ”‚ 1      โ”‚ 12.0    โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 12.0     โ”‚ 12.0      โ”‚ 1        โ”‚ 52    โ”‚
โ”‚ 3     โ”‚ 1      โ”‚ 24.0    โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 12.0     โ”‚ 24.0      โ”‚ 1        โ”‚ 52    โ”‚
โ”‚ 4     โ”‚ 1      โ”‚ 36.0    โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 12.0     โ”‚ 36.0      โ”‚ 1        โ”‚ 52    โ”‚
โ‹ฎ
โ”‚ 14308 โ”‚ 249    โ”‚ 696.0   โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 8.0      โ”‚ 696.0     โ”‚ 1        โ”‚ 55    โ”‚
โ”‚ 14309 โ”‚ 249    โ”‚ 704.0   โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 8.0      โ”‚ 704.0     โ”‚ 1        โ”‚ 55    โ”‚
โ”‚ 14310 โ”‚ 249    โ”‚ 712.0   โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 8.0      โ”‚ 712.0     โ”‚ 1        โ”‚ 55    โ”‚
โ”‚ 14311 โ”‚ 249    โ”‚ 720.0   โ”‚ 1     โ”‚ missing  โ”‚ 500.0    โ”‚ 500.0   โ”‚ 0.0     โ”‚ 1      โ”‚ 0     โ”‚ 8.0      โ”‚ 720.0     โ”‚ 1        โ”‚ 55    โ”‚
โ”‚ 14312 โ”‚ 249    โ”‚ 733.75  โ”‚ 0     โ”‚ 4.42     โ”‚ missing  โ”‚ 500.0   โ”‚ 13.75   โ”‚ 1      โ”‚ 0     โ”‚ missing  โ”‚ missing   โ”‚ missing  โ”‚ 55    โ”‚

Could you please try to pass optimize_fn=Pumas.DefaultOptimizeFN(extended_trace=true) to the fit function and show the output of the last iteration before you hit the warnings?

result  = fit(jef,jd2, param, Pumas.FOCEI())
optimize_fn=Pumas.DefaultOptimizeFN(extended_trace=true)

is this the code you want me to run?

No, itโ€™s

result  = fit(jef,jd2, param, Pumas.FOCEI(),
    optimize_fn=Pumas.DefaultOptimizeFN(extended_trace=true))

its part of error, and the code is still running

โ”Œ Warning: `CSV.read(input; kw...)` is deprecated in favor of `using DataFrames; CSV.read(input, DataFrame; kw...)
โ”‚   caller = ip:0x0
โ”” @ Core :-1
Iter     Function value   Gradient norm
     0     1.314568e+03     9.364355e+02
 * Current step size: 1.0
 * time: 0.002000093460083008
 * g(x): [936.4355290659157, -82.65376328136328, 2.527936530898093, -576.4865233168487, -52.925102954263934, -0.0036118965139051275, -20.623717105162527]
 * ~inv(H): [0.0009056126078278203 0.0 0.0 0.0 0.0 0.0 0.0; 0.0 0.0009056126078278203 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0009056126078278203 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0009056126078278203 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0009056126078278203 0.0 0.0; 0.0 0.0 0.0 0.0 0.0 0.0009056126078278203 0.0; 0.0 0.0 0.0 0.0 0.0 0.0 0.0009056126078278203]
 * x: [-0.6190392084062233, -0.6632942174102644, 0.5753641449035619, -3.506557897319982, -0.3285040669720361, -4.605170185988091, -0.6931471805599454]
     1     9.266626e+02     2.255018e+02
 * Current step size: 1.0
 * time: 166.06500005722046
 * g(x): [-225.50182571044067, 110.5023838140857, -3.614638759951394, -65.45410434207267, -66.72652304804703, -0.003687870348179383, -0.7481395995874063]
 * ~inv(H): [0.0007339700341822807 7.009492332531254e-5 -2.286325257992084e-6 -1.8220918406626138e-5 -3.849586781172116e-5 -2.102021846356349e-9 3.145359138417367e-7; 7.009492332531254e-5 0.0008945760529046027 3.5012652559361807e-7 -3.2216887376831864e-5 2.924465403758927e-7 -2.639340480359203e-11 -1.2378515741225478e-6; -2.286325257992084e-6 3.5012652559361807e-7 0.0009056015146565128 1.0730656513422784e-6 -8.908149009458182e-10 1.356851803279053e-12 4.099754942325131e-8; -1.8220918406626138e-5 -3.221688737683188e-5 1.0730656513422788e-6 0.0009930968971813994 3.070055464199134e-5 1.77188375023881e-9 2.534812190383563e-6; -3.849586781172115e-5 2.9244654037589183e-7 -8.908149009457918e-10 3.070055464199134e-5 0.0009105122648383853 3.046992502486431e-10 1.0436897824441007e-6; -2.1020218463563483e-9 -2.6393404803592083e-11 1.3568518032790547e-12 1.77188375023881e-9 3.046992502486431e-10 0.0009056126078465891 5.966145046930583e-11; 3.145359138417367e-7 -1.2378515741225482e-6 4.099754942325131e-8 2.534812190383563e-6 1.043689782444101e-6 5.966145046930585e-11 0.0009056820069998166]
 * x: [-1.467087029946232, -0.5884419272982456, 0.5730748137093921, -2.984484433561417, -0.2805744264660693, -4.60516691500907, -0.6744700823292359]

its still running. part of the error is

โ”Œ Warning: `CSV.read(input; kw...)` is deprecated in favor of `using DataFrames; CSV.read(input, DataFrame; kw...)
โ”‚   caller = ip:0x0
โ”” @ Core :-1
Iter     Function value   Gradient norm
     0     1.314568e+03     9.364355e+02
 * Current step size: 1.0
 * time: 0.002000093460083008
 * g(x): [936.4355290659157, -82.65376328136328, 2.527936530898093, -576.4865233168487, -52.925102954263934, -0.0036118965139051275, -20.623717105162527]
 * ~inv(H): [0.0009056126078278203 0.0 0.0 0.0 0.0 0.0 0.0; 0.0 0.0009056126078278203 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0009056126078278203 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0009056126078278203 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0009056126078278203 0.0 0.0; 0.0 0.0 0.0 0.0 0.0 0.0009056126078278203 0.0; 0.0 0.0 0.0 0.0 0.0 0.0 0.0009056126078278203]
 * x: [-0.6190392084062233, -0.6632942174102644, 0.5753641449035619, -3.506557897319982, -0.3285040669720361, -4.605170185988091, -0.6931471805599454]
     1     9.266626e+02     2.255018e+02
 * Current step size: 1.0
 * time: 166.06500005722046
 * g(x): [-225.50182571044067, 110.5023838140857, -3.614638759951394, -65.45410434207267, -66.72652304804703, -0.003687870348179383, -0.7481395995874063]
 * ~inv(H): [0.0007339700341822807 7.009492332531254e-5 -2.286325257992084e-6 -1.8220918406626138e-5 -3.849586781172116e-5 -2.102021846356349e-9 3.145359138417367e-7; 7.009492332531254e-5 0.0008945760529046027 3.5012652559361807e-7 -3.2216887376831864e-5 2.924465403758927e-7 -2.639340480359203e-11 -1.2378515741225478e-6; -2.286325257992084e-6 3.5012652559361807e-7 0.0009056015146565128 1.0730656513422784e-6 -8.908149009458182e-10 1.356851803279053e-12 4.099754942325131e-8; -1.8220918406626138e-5 -3.221688737683188e-5 1.0730656513422788e-6 0.0009930968971813994 3.070055464199134e-5 1.77188375023881e-9 2.534812190383563e-6; -3.849586781172115e-5 2.9244654037589183e-7 -8.908149009457918e-10 3.070055464199134e-5 0.0009105122648383853 3.046992502486431e-10 1.0436897824441007e-6; -2.1020218463563483e-9 -2.6393404803592083e-11 1.3568518032790547e-12 1.77188375023881e-9 3.046992502486431e-10 0.0009056126078465891 5.966145046930583e-11; 3.145359138417367e-7 -1.2378515741225482e-6 4.099754942325131e-8 2.534812190383563e-6 1.043689782444101e-6 5.966145046930585e-11 0.0009056820069998166]
 * x: [-1.467087029946232, -0.5884419272982456, 0.5730748137093921, -2.984484433561417, -0.2805744264660693, -4.60516691500907, -0.6744700823292359]
     2     8.898840e+02     7.883795e+01
 * Current step size: 1.0
 * time: 316.3010001182556
 * g(x): [-64.63729684837365, 65.52903241699343, -2.20895096704347, -78.83795486895163, -26.93598847305928, -0.00186277495524039, -1.2181097581650808]
 * ~inv(H): [0.0009125048347899914 -0.0002054912411155352 7.0479320117728295e-6 0.00038179750923969345 7.712412631989015e-5 6.089649232866492e-9 7.486397644997335e-6; -0.0002054912411155353 0.0011447194323092969 -8.014163095945413e-6 -0.0003297551586756317 -0.00012571293443035855 -8.00675164961305e-9 -6.490337924632865e-6; 7.047932011772833e-6 -8.014163095945413e-6 0.0009058810859977499 1.095331698855638e-5 4.234587705798238e-6 2.687761380787321e-10 2.1530995912261133e-7; 0.00038179750923969356 -0.0003297551586756317 1.0953316988556382e-5 0.001305315348465751 0.00019397593066233047 1.1610926795942891e-8 7.982780188218344e-6; 7.71241263198902e-5 -0.00012571293443035855 4.234587705798238e-6 0.00019397593066233047 0.0009696815407611266 4.2132980030084204e-9 3.946469499096948e-6; 6.089649232866494e-9 -8.006751649613046e-9 2.6877613807873214e-10 1.1610926795942891e-8 4.2132980030084204e-9 0.0009056126080983057 2.3388084161585125e-10; 7.486397644997335e-6 -6.490337924632865e-6 2.153099591226113e-7 7.982780188218344e-6 3.946469499096948e-6 2.3388084161585125e-10 0.0009057769595735957]
 * x: [-1.3130904615783496, -0.6735770545363998, 0.5758641834918035, -2.917976656732609, -0.22652205844079992, -4.605163909962291, -0.6733490879391227]
     3     8.691840e+02     8.144390e+01
 * Current step size: 1.0
 * time: 462.1400001049042
 * g(x): [25.63646462402934, 31.102203181242803, -1.1674293822828057, -81.44389583639699, -3.698917549559954, -0.0007696496914886553, -1.2063064116143134]
 * ~inv(H): [0.0009364237418761109 -0.0005344754549702563 1.879926208997637e-5 0.001045337400570944 0.00019018012385153103 1.6035540104524896e-8 1.8232951931857434e-5; -0.0005344754549702564 0.0018545047918595867 -3.266121531272082e-5 -0.001521912331132027 -0.00041062156005133616 -2.9686067190269696e-8 -2.6511714681180593e-5; 1.8799262089976384e-5 -3.266121531272082e-5 0.0009067361123109043 5.2067894701954886e-5 1.4176332955799714e-5 1.0218438101268346e-9 9.0680959165693e-7; 0.001045337400570944 -0.001521912331132027 5.206789470195488e-5 0.003211869647463949 0.0006889087792907488 4.811197617391784e-8 4.034468914341037e-5; 0.00019018012385153108 -0.00041062156005133616 1.4176332955799714e-5 0.0006889087792907488 0.0010812366571527768 1.2900262254637245e-8 1.2199811068725573e-5; 1.60355401045249e-8 -2.9686067190269693e-8 1.0218438101268346e-9 4.811197617391784e-8 1.2900262254637245e-8 0.0009056126087603859 8.46571939000546e-10; 1.8232951931857434e-5 -2.6511714681180593e-5 9.0680959165693e-7 4.034468914341038e-5 1.2199811068725573e-5 8.46571939000546e-10 0.0009063249834425982]
 * x: [-1.2084407363143186, -0.7912808429986831, 0.5798238122073696, -2.7635225160806955, -0.17187295872900427, -4.605160274966977, -0.6706004223840574]
     4     8.496392e+02     6.609623e+01
 * Current step size: 1.0
 * time: 603.5920000076294
 * g(x): [65.78128727680478, -0.3694756408223463, -0.28643882828502676, -66.09622738017256, 12.528190973453007, 2.251099017896645e-6, -0.7567718642634884]
 * ~inv(H): [0.0008511978581665793 -0.0006257080907337374 2.3118080900227426e-5 0.0013907947059868808 0.00020097826094275938 1.955309847862236e-8 2.2539616363223646e-5; -0.0006257080907337375 0.0026459470601330323 -6.262946964873243e-5 -0.0032665248190620094 -0.000672508572678951 -5.543780970333201e-8 -5.258198625663475e-5; 2.3118080900227433e-5 -6.262946964873242e-5 0.0009078630697299925 0.00011682526459557616 2.4267819042080885e-5 1.9919867952592324e-9 1.8822220493791957e-6; 0.0013907947059868808 -0.0032665248190620094 0.00011682526459557614 0.006839967159401022 0.0012954331067414789 1.0404992577117153e-7 9.585042838580206e-5; 0.00020097826094275933 -0.0006725085726789507 2.4267819042080885e-5 0.0012954331067414789 0.0011639675143373432 2.1532672851028603e-8 2.109000236019841e-5; 1.9553098478622364e-8 -5.5437809703332026e-8 1.9919867952592324e-9 1.0404992577117155e-7 2.1532672851028603e-8 0.0009056126095951407 1.6873762749695152e-9; 2.2539616363223646e-5 -5.2581986256634734e-5 1.8822220493791953e-6 9.585042838580204e-5 2.109000236019841e-5 1.6873762749695147e-9 0.0009071660528790864]
 * x: [-1.1299402139363839, -0.9607974023421457, 0.5857103948944293, -2.4787415973574305, -0.10383918285942992, -4.605155097397037, -0.6658179590437956]
     5     8.364468e+02     6.239177e+01
 * Current step size: 1.0
 * time: 739.3450000286102
 * g(x): [62.39176665761764, -20.584612928048035, 0.22134710813088584, -39.729912034341055, 20.85273147089983, 0.0003890067791600428, -0.2885258116987914]
 * ~inv(H): [0.0007539528883482079 -0.0003925425082121066 1.5452411746216905e-5 0.001022735297147194 0.00010174866060049792 1.2752891760793423e-8 1.6258670112086232e-5; -0.0003925425082121067 0.0027356962163797324 -7.0856003943577e-5 -0.004029868535851754 -0.0006139185611984768 -6.166182983845084e-8 -6.105521959477012e-5; 1.5452411746216912e-5 -7.085600394357699e-5 0.0009083498839356753 0.0001553046997671688 2.3799859097312942e-5 2.3798075288369855e-9 2.3521546084884447e-6; 0.0010227352971471939 -0.0040298685358517525 0.00015530469976716876 0.009621924400060124 0.0013747789825440749 1.3546126162130178e-7 0.00013177438788827822; 0.00010174866060049786 -0.0006139185611984768 2.379985909731295e-5 0.0013747789825440753 0.0011122813222188836 2.0820763782960525e-8 2.1185508456338808e-5; 1.2752891760793426e-8 -6.166182983845085e-8 2.3798075288369855e-9 1.3546126162130183e-7 2.0820763782960525e-8 0.0009056126099018926 2.065307641861598e-9; 1.6258670112086232e-5 -6.105521959477012e-5 2.3521546084884443e-6 0.0001317743878882782 2.1185508456338808e-5 2.0653076418615977e-9 0.0009076139452038222]
 * x: [-1.0967322203167302, -1.1261972891219811, 0.5918456667376214, -2.135464173320655, -0.046244521676266345, -4.605149796756913, -0.6605618827675774]
     6     8.309963e+02     4.183546e+01
 * Current step size: 1.0
 * time: 854.6110000610352
 * g(x): [41.83545560692398, -23.755189977056638, 0.28654525164734507, -22.07316078827811, 23.76200882213798, 0.0005096905857745383, -0.07539462184232042]
 * ~inv(H): [0.0008994936924555716 -0.00016216792107743357 2.5469963649649605e-6 5.89764708316963e-5 0.00011193782005598522 2.7980414778624677e-9 4.116993676697712e-6; -0.00016216792107743362 0.0022470965942680303 -5.779588976830794e-5 -0.0034998941331055126 -0.00030914028885938635 -4.782935131189475e-8 -5.060583977974277e-5; 2.5469963649649673e-6 -5.7795889768307926e-5 0.0009081799277519897 0.00016009083650708972 1.156766201903026e-5 2.101205762662368e-9 2.2643864654361803e-6; 5.89764708316963e-5 -0.00349989413310551 0.0001600908365070897 0.011052163944565627 0.0006119492450340123 1.3009940129163647e-7 0.0001407046409174925; 0.00011193782005598516 -0.00030914028885938635 1.1567662019030266e-5 0.0006119492450340127 0.0010153466213577537 1.0113811008386913e-8 1.029893647476809e-5; 2.798041477862471e-9 -4.7829351311894763e-8 2.1012057626623682e-9 1.3009940129163652e-7 1.0113811008386915e-8 0.0009056126095566545 1.8669274802299717e-9; 4.1169936766977155e-6 -5.060583977974277e-5 2.26438646543618e-6 0.00014070464091749249 1.029893647476809e-5 1.8669274802299713e-9 0.0009075952740486044]
 * x: [-1.1133402919993154, -1.1926989965924275, 0.5948965880807268, -1.928613762220201, -0.033803487479044256, -4.605147266243361, -0.6577781294548781]
     7     8.272452e+02     2.508415e+01
 * Current step size: 1.0
 * time: 965.8960001468658
 * g(x): [13.877949017677446, -18.96258484762019, 0.16258580097833314, -9.321464663501768, 25.084148981158837, 0.0005628303694046705, 0.05298274468547949]
 * ~inv(H): [0.001244024005027714 -0.0004326571780166884 6.070098961117395e-7 -0.0005268025260671171 0.0005516570270202316 8.160928665803816e-9 1.1637895448113737e-6; -0.00043265717801668844 0.002106450342947407 -4.58692343878688e-5 -0.002462598293726528 -0.0003936297439585398 -3.9154088092197375e-8 -3.862281786296329e-5; 6.070098961117463e-7 -4.5869234387868785e-5 0.0009078842435662432 0.00014637237700577886 1.407546533756828e-6 1.691250639200268e-9 1.996190003918305e-6; -0.0005268025260671171 -0.0024625982937265256 0.00014637237700577884 0.01110367603467165 -0.0005621453088239655 9.990456813875778e-8 0.0001299178166371125; 0.0005516570270202316 -0.0003936297439585398 1.4075465337568347e-6 -0.0005621453088239651 0.0013839759432943534 7.440986774345931e-9 -6.08426820595904e-7; 8.160928665803819e-9 -3.915408809219739e-8 1.6912506392002684e-9 9.990456813875783e-8 7.440986774345932e-9 0.0009056126091697727 1.4681801191129918e-9; 1.163789544811377e-6 -3.862281786296329e-5 1.9961900039183047e-6 0.00012991781663711246 -6.084268205959074e-7 1.4681801191129914e-9 0.0009073559975464402]
 * x: [-1.1561818399883945, -1.2024296071525227, 0.5964158569495849, -1.784841936293583, -0.056451702945837165, -4.605146350159047, -0.6562236654034016]
     8     8.249015e+02     2.450380e+01
 * Current step size: 1.0
 * time: 1079.8250000476837
 * g(x): [-12.690468713281101, -10.729335165948884, -0.03973040429104191, -2.8574282898553927, 24.503804899453687, 0.0005604405498383552, 0.12114389808017911]
 * ~inv(H): [0.0012357300380629382 -0.0008019955150839995 2.703121598371083e-6 -0.0006354172532903843 0.0011637577565640936 2.290920940138409e-8 4.834366962787492e-6; -0.0008019955150839999 0.0026602559783781925 -4.485322643712213e-5 -0.0017178618613660436 -0.0013164593208228525 -5.5394876929084765e-8 -3.7705833383266794e-5; 2.703121598371088e-6 -4.485322643712212e-5 0.0009078558910465248 0.00014351119480916834 -2.490490662401393e-7 1.6187823116267342e-9 1.9512231197285946e-6; -0.0006354172532903843 -0.001717861861366041 0.0001435111948091683 0.01151371986004969 -0.0017980353530205554 7.209435624627481e-8 0.0001246244367377895; 0.0011637577565640936 -0.0013164593208228525 -2.4904906624013254e-7 -0.0017980353530205558 0.0029216817041587823 3.4555130466867126e-8 -2.0802084874845706e-6; 2.2909209401384092e-8 -5.539487692908478e-8 1.6187823116267349e-9 7.209435624627486e-8 3.4555130466867126e-8 0.0009056126095857818 1.3754087308642965e-9; 4.834366962787495e-6 -3.7705833383266794e-5 1.951223119728594e-6 0.00012462443673778948 -2.0802084874845706e-6 1.375408730864296e-9 0.000907285497373318]
 * x: [-1.200399218695214, -1.169553121321788, 0.5967190166297265, -1.7066554478459657, -0.11152788145546527, -4.605146971331677, -0.6557943174343321]
     9     8.231946e+02     3.046274e+01
 * Current step size: 1.0
 * time: 1190.0190000534058
 * g(x): [-30.462741015649037, -4.179283682666151, -0.19955569233772208, -0.25198134183363635, 22.561493440219266, 0.000530469319983923, 0.15461308331415588]
 * ~inv(H): [0.0008228467465343351 -0.0007272486308155636 -2.6057446653831994e-9 -0.0005373625680051849 0.0012707937435431933 2.6835036184077243e-8 6.068058003498043e-6; -0.0007272486308155644 0.003962026777449425 -3.9373527948705645e-5 -0.0003118279350152271 -0.00393792158310888 -1.0912394476868342e-7 -4.1587653067633493e-5; -2.6057446653781172e-9 -3.937352794870563e-5 0.0009078570897830595 0.00014955518587644894 -9.419144087495622e-6 1.443373534098078e-9 1.9454286430406333e-6; -0.0005373625680051853 -0.0003118279350152245 0.00014955518587644892 0.013031648522805896 -0.004640153010367676 1.3770857099243047e-8 0.00012037123210032972; 0.0012707937435431933 -0.003937921583108879 -9.419144087495615e-6 -0.004640153010367675 0.008041680714830742 1.3842446826362797e-7 4.837593519913709e-6; 2.683503618407726e-8 -1.0912394476868343e-7 1.4433735340980785e-9 1.37708570992431e-8 1.38424468263628e-7 0.000905612611685563 1.511147422713636e-9; 6.068058003498047e-6 -4.1587653067633493e-5 1.945428643040633e-6 0.0001203712321003297 4.837593519913709e-6 1.5111474227136357e-9 0.0009072919870653741]
 * x: [-1.223654734515309, -1.123835661194273, 0.5967240839096762, -1.6562017657284884, -0.1876138167919087, -4.605148423325331, -0.6558402817413643]
    10     8.202200e+02     4.793679e+01
 * Current step size: 1.0
 * time: 1299.25200009346
 * g(x): [-47.9367860075297, 2.7203898240064195, -0.3664201158303184, 2.1051328231609934, 18.27974607981614, 0.0004669187558988413, 0.1855855537026322]
 * ~inv(H): [0.0006544774783152369 0.00021329815320587898 2.1151460932366027e-6 0.00047032156098429504 -0.0004847910027592343 -8.307919791775738e-9 3.881893944693516e-6; 0.00021329815320587822 0.0062203213277668675 -2.1158313566683655e-5 0.0023074333667088094 -0.009000517556464607 -2.152219571712563e-7 -4.921585937980205e-5; 2.1151460932366077e-6 -2.1158313566683642e-5 0.0009079506178550948 0.00016986958203326708 -4.6807861369508694e-5 6.759122563117497e-10 1.8935748199889787e-6; 0.0004703215609842948 0.0023074333667088102 0.00016986958203326702 0.016057214555213584 -0.010459532410038858 -1.0794225312608873e-7 0.00011167092102343156; -0.0004847910027592345 -0.009000517556464605 -4.680786136950869e-5 -0.010459532410038856 0.019168530068369043 3.705732788439191e-7 2.1313996484250693e-5; -8.307919791775722e-9 -2.152219571712563e-7 6.759122563117504e-10 -1.0794225312608868e-7 3.7057327884391914e-7 0.0009056126165241253 1.8535295529095718e-9; 3.881893944693519e-6 -4.9215859379802044e-5 1.8935748199889783e-6 0.00011167092102343153 2.1313996484250693e-5 1.8535295529095714e-9 0.0009073160011164467]
 * x: [-1.2304352943012156, -1.0406658240420636, 0.596990513723233, -1.5658907722696203, -0.34796383386430796, -4.605151661854545, -0.6560479416827132]
    11     8.147655e+02     5.687178e+01
 * Current step size: 1.0
 * time: 1404.4230000972748
 * g(x): [-56.87178339723675, 6.570941914150329, -0.44982151353031297, 5.401441315566142, 11.516689992621046, 0.00037002505814152296, 0.20912953887328378]
 * ~inv(H): [0.0014935106929054604 0.002367182494325385 1.4576606899481475e-5 0.0025899378495196136 -0.005080366878217677 -1.0775397611408442e-7 -6.60636896285641e-6; 0.0023671824943253842 0.010130131450993226 -1.6817732074593964e-6 0.005456680462174073 -0.01731956070100258 -4.0419475475100584e-7 -7.646934636361977e-5; 1.457660689948148e-5 -1.6817732074593829e-6 0.000908039007542142 0.00018364005595589427 -8.818560543814043e-5 -2.886595168616157e-10 1.7352589114698907e-6; 0.002589937849519613 0.0054566804621740735 0.0001836400559558942 0.018167952165243646 -0.017146262368121317 -2.6531087121723914e-7 8.470913975228054e-5; -0.005080366878217678 -0.01731956070100258 -8.818560543814041e-5 -0.017146262368121314 0.03686879378559749 7.728273999773225e-7 7.946732307486505e-5; -1.077539761140844e-7 -4.0419475475100584e-7 -2.886595168616151e-10 -2.6531087121723914e-7 7.728273999773225e-7 0.0009056126255953227 3.1101205995476495e-9; -6.60636896285641e-6 -7.646934636361975e-5 1.7352589114698903e-6 8.470913975228051e-5 7.946732307486507e-5 3.1101205995476495e-9 0.0009074470418943475]
 * x: [-1.1917701799126628, -0.8876915921352574, 0.5979798436274937, -1.3921856401633428, -0.6751165045172249, -4.605158444318394, -0.6565203573046742]
    12     8.075830e+02     4.342982e+01
 * Current step size: 1.0
 * time: 1501.582999944687
 * g(x): [-43.42982269687632, 2.725473278226484, -0.31546546868496306, 10.348972012990076, 5.733398481053677, 0.00030292462393065556, 0.20828222438417432]
 * ~inv(H): [0.0035216694574261133 0.006384999795319835 8.711082854014631e-6 0.0037518690509028177 -0.012547010800538484 -2.967503624993887e-7 -5.284481778142661e-5; 0.006384999795319834 0.018065440236171484 -1.640646251076043e-5 0.007476196229444923 -0.031940843586526976 -7.773191318382312e-7 -0.0001703217171699948; 8.711082854014636e-6 -1.6406462510760415e-5 0.0009076552037971299 0.00014384394500274565 -4.46150457674925e-5 4.2322978620576884e-10 1.5781558447316604e-6; 0.0037518690509028172 0.007476196229444924 0.0001438439450027456 0.015521064038061368 -0.01942588685760641 -3.585582411690161e-7 3.177863552106694e-5; -0.012547010800538484 -0.031940843586526976 -4.461504576749249e-5 -0.019425886857606406 0.06315203326643758 1.4595508159028911e-6 0.0002656415996130375; -2.9675036249938876e-7 -7.773191318382314e-7 4.2322978620576864e-10 -3.585582411690162e-7 1.4595508159028911e-6 0.0009056126431389934 7.538862045180811e-9; -5.2844817781426626e-5 -0.0001703217171699948 1.5781558447316598e-6 3.17786355210669e-5 0.00026564159961303755 7.538862045180811e-9 0.0009082901514408811]
 * x: [-1.0778586303764788, -0.6496248996449022, 0.5992516699729442, -1.1813468351902099, -1.1822884273498253, -4.605169719771038, -0.6579553430536484]
    13     8.010279e+02     1.975954e+01
 * Current step size: 1.0
 * time: 1599.2030000686646
 * g(x): [-19.759542560243013, -1.4346379890424816, -0.155256787835041, 7.888744773257083, 2.23324761417221, 0.0001961601268262168, 0.17408729825152175]
 * ~inv(H): [0.006338677977582731 0.012395338576745537 -1.8841266882060828e-5 0.00394029796102794 -0.02282364117764136 -5.739916659893556e-7 -0.00013677726393455055; 0.012395338576745536 0.03082202929618417 -7.229178773095798e-5 0.008089632307604122 -0.053876385304239535 -1.366527383225146e-6 -0.00034642664688409533; -1.884126688206082e-5 -7.229178773095795e-5 0.0009077991654449411 0.00013285095302781864 5.630607166964744e-5 3.034832570727495e-9 2.2704232637949376e-6; 0.00394029796102794 0.008089632307604124 0.00013285095302781859 0.014866659149883766 -0.020083520102558827 -3.843935963924516e-7 1.6786101235426595e-5; -0.02282364117764136 -0.053876385304239535 5.630607166964746e-5 -0.02008352010255882 0.10064052106601294 2.47127050702466e-6 0.000572251165709787; -5.739916659893557e-7 -1.3665273832251463e-6 3.0348325707274946e-9 -3.843935963924517e-7 2.47127050702466e-6 0.0009056126703445368 1.5696724925559648e-8; -0.00013677726393455057 -0.0003464266468840953 2.270423263794937e-6 1.6786101235426554e-5 0.0005722511657097871 1.5696724925559648e-8 0.0009106590475089385]
 * x: [-0.9091925169337863, -0.3157734271280369, 0.5987278701788514, -1.0879919487316856, -1.8012561816739905, -4.605185422270439, -0.6618267650265794]
    14     7.979475e+02     3.877372e+00
 * Current step size: 1.0
 * time: 1695.819000005722
 * g(x): [2.9717619804191653, -3.877371993312331, -0.028367510957537687, 0.1308734923625711, 0.8415717540149016, 9.97808230716599e-5, 0.12502021674637395]
 * ~inv(H): [0.009006882869614244 0.019215956311631012 -3.528812567375001e-5 0.00557624424425144 -0.03477434807168979 -8.820953439579651e-7 -0.0002208926156535091; 0.01921595631163101 0.047753224625237595 -0.00011792754692075555 0.011681863719429211 -0.08346385553222593 -2.1338614888093036e-6 -0.0005588246435187343; -3.528812567375e-5 -0.00011792754692075552 0.0009078749275560372 0.00011856328662196454 0.0001368256140736832 5.0784061825067965e-9 2.807606921479557e-6; 0.00557624424425144 0.011681863719429211 0.00011856328662196448 0.015179881726442652 -0.026285879456274405 -5.496012156022854e-7 -3.171934553844188e-5; -0.03477434807168979 -0.08346385553222593 0.00013682561407368318 -0.0262858794562744 0.15233241973183126 3.8125985960031392e-6 0.0009439950776101258; -8.820953439579652e-7 -2.133861488809304e-6 5.078406182506796e-9 -5.496012156022856e-7 3.81259859600314e-6 0.0009056127051077925 2.530431828555562e-8; -0.00022089261565350911 -0.0005588246435187342 2.807606921479556e-6 -3.1719345538441914e-5 0.0009439950776101259 2.5304318285555613e-8 0.0009132971460621746]
 * x: [-0.7462525927269068, 0.029922596468513307, 0.5972186368874709, -1.0709378721154437, -2.3959463195394206, -4.605201391037797, -0.6665949995191826]
    15     7.973997e+02     1.160156e+01
 * Current step size: 1.0
 * time: 1786.1159999370575
 * g(x): [11.601561449537744, -4.989016527140964, 0.050621768607691665, 0.3185108647466426, 0.5543771993304053, 0.00010305262474210485, 0.11307091212469629]
 * ~inv(H): [0.010736964095750394 0.028546673543408084 -8.541129927332357e-5 0.006352914298536168 -0.04940700768835497 -1.279936046494133e-6 -0.0003536444015659568; 0.02854667354340808 0.08437958374060109 -0.00027642036990192234 0.016802790296233668 -0.14322935559944133 -3.7267885479501182e-6 -0.001055318630091816; -8.541129927332357e-5 -0.0002764203699019223 0.0009084139404434869 8.845059655106179e-5 0.00040437950557295477 1.2091440723660989e-8 4.861653570372143e-6; 0.006352914298536168 0.016802790296233668 8.845059655106173e-5 0.015465101816781571 -0.03415825656128701 -7.658182731931608e-7 -0.00010625130716264751; -0.04940700768835497 -0.14322935559944133 0.00040437950557295477 -0.03415825656128701 0.249312222721134 6.404578382319285e-6 0.0017598987552113186; -1.279936046494133e-6 -3.7267885479501195e-6 1.2091440723660987e-8 -7.65818273193161e-7 6.404578382319286e-6 0.000905612774288183 4.697463277604221e-8; -0.00035364440156595683 -0.001055318630091816 4.861653570372142e-6 -0.00010625130716264755 0.0017598987552113186 4.6974632776042207e-8 0.0009199667184810506]
 * x: [-0.6699495523361677, 0.2267528601112929, 0.5967609936104444, -1.022072073034358, -2.7410983242109452, -4.605210273464493, -0.6690097196007594]
    16     7.970365e+02     1.419191e+01
 * Current step size: 1.0
 * time: 1872.6760001182556
 * g(x): [14.19191320893247, -4.697184907621543, 0.06745414461415421, -0.49387523490263296, 0.3830407922609408, 8.825067583722118e-5, 0.10707978527198406]
 * ~inv(H): [0.010757574239806411 0.037919362254275286 -0.00013184799797357532 0.008073542246378726 -0.06356734758923607 -1.6610327725811266e-6 -0.00048671513017891884; 0.03791936225427528 0.1551261330163863 -0.0006000065371167242 0.028510546463933792 -0.2546684369146592 -6.707036816471611e-6 -0.0020340328640973985; -0.00013184799797357532 -0.0006000065371167241 0.0009098835639507816 3.539604193268234e-5 0.0009158510814549595 2.576285765697166e-8 9.328218333524384e-6; 0.008073542246378726 0.028510546463933792 3.5396041932682313e-5 0.01737906053700281 -0.05268395171838159 -1.2609228081376522e-6 -0.0002677442551118933; -0.06356734758923607 -0.2546684369146592 0.0009158510814549593 -0.05268395171838159 0.42455150537742087 1.109224149596616e-5 0.003303241286986234; -1.661032772581127e-6 -6.707036816471613e-6 2.5762857656971656e-8 -1.2609228081376524e-6 1.109224149596616e-5 0.0009056128996787652 8.824199242837116e-8; -0.000486715130178919 -0.002034032864097399 9.328218333524382e-6 -0.00026774425511189335 0.003303241286986234 8.824199242837116e-8 0.0009334968287732327]
 * x: [-0.6266843179508759, 0.39072254751653723, 0.5960739457666658, -0.9979281080235779, -3.01002621111275, -4.605217423097572, -0.671217967565255]
    17     7.963868e+02     1.454017e+01
 * Current step size: 1.0
 * time: 1958.0110001564026
 * g(x): [14.540171130850336, -3.7167092481408663, 0.0725347563057816, -0.2402721005649457, 0.20614753883484838, 7.283369189362835e-5, 0.10684230568872317]
 * ~inv(H): [0.008862652752000455 0.03861152044723704 -0.00015886273597349518 0.006897723850977259 -0.06302202932393466 -1.6679736497903059e-6 -0.0005178655270052519; 0.03861152044723702 0.22267559257005862 -0.001034441927351323 0.032039172098928585 -0.353318650292425 -9.460452524869206e-6 -0.003081597330948176; -0.00015886273597349518 -0.001034441927351323 0.000912409914587755 -1.6752673993784237e-6 0.0015687672183854599 4.372343722650244e-8 1.5823295359952886e-5; 0.006897723850977261 0.032039172098928585 -1.6752673993784508e-6 0.01679110954137642 -0.05684561547359867 -1.391199820685624e-6 -0.0003354759847029095; -0.06302202932393468 -0.3533186502924251 0.0015687672183854599 -0.05684561547359868 0.5673485236305571 1.5095965480874431e-5 0.004849823547608351; -1.6679736497903063e-6 -9.460452524869208e-6 4.372343722650243e-8 -1.3911998206856237e-6 1.5095965480874431e-5 0.0009056130116741388 1.3117060726645413e-7; -0.0005178655270052521 -0.0030815973309481766 1.5823295359952886e-5 -0.00033547598470290955 0.004849823547608349 1.3117060726645413e-7 0.000949523423897498]
 * x: [-0.5728434008653682, 0.6931177102417269, 0.5947310780813555, -0.9497983376047654, -3.4931640028311355, -4.60523031668395, -0.6753628734423625]
    18     7.956413e+02     1.096546e+01
 * Current step size: 1.0
 * time: 2044.016000032425
 * g(x): [10.96545638184239, -2.3235698785365444, 0.040394399417991916, -0.5105462584950098, 0.10163953297145274, 4.75343646643963e-5, 0.11166954906503777]
 * ~inv(H): [0.008186312044779468 0.038692513765606486 -0.0001625343497478074 0.006808197788570846 -0.0627357384091233 -1.6641400762260756e-6 -0.0005256330074478588; 0.038692513765606465 0.3191457603507484 -0.0016079134860224262 0.040493673257115004 -0.49522980218338314 -1.3387755614706205e-5 -0.004578453603087894; -0.00016253434974780742 -0.0016079134860224262 0.0009158038982132112 -5.2389165238390356e-5 0.002414277048248869 6.710311063804895e-8 2.4690722844890978e-5; 0.006808197788570848 0.040493673257115004 -5.238916523839038e-5 0.017518246718835513 -0.06922458056181124 -1.7343641587155907e-6 -0.0004675882841614292; -0.0627357384091233 -0.49522980218338325 0.002414277048248869 -0.06922458056181127 0.7758620131233402 2.086889807530926e-5 0.007055656487347885; -1.664140076226076e-6 -1.3387755614706207e-5 6.710311063804895e-8 -1.7343641587155902e-6 2.0868898075309263e-5 0.0009056131714795775 1.9217630341343975e-7; -0.000525633007447859 -0.004578453603087895 2.4690722844890978e-5 -0.00046758828416142915 0.007055656487347885 1.9217630341343975e-7 0.000972686366692616]
 * x: [-0.543484073447166, 1.0402581975659588, 0.5928045775182319, -0.9152231520405533, -4.021243481353326, -4.605244755220842, -0.680469403083917]
    19     7.950054e+02     5.336727e+00
 * Current step size: 1.0
 * time: 2132.726000070572
 * g(x): [5.336727205075633, -1.2400061540666978, 0.0010270002560765568, 0.14642265800131837, 0.04883249123239226, 2.9627526854619413e-5, 0.12214442885369055]
 * ~inv(H): [0.008370621800643657 0.044852471497035154 -0.00019910530829700916 0.0072685249500436125 -0.07185856861268151 -1.916778928716379e-6 -0.0006218612683576813; 0.04485247149703513 0.519944408036545 -0.0028041597676466898 0.05488247039073544 -0.792421696456177 -2.1624597049020343e-5 -0.007728195138437066; -0.0001991053082970092 -0.0028041597676466898 0.0009229270256017324 -0.00013862355365549958 0.004184937779847329 1.1617238993773945e-7 4.3444332169500875e-5; 0.007268524950043614 0.05488247039073543 -0.00013862355365549953 0.01847253408000895 -0.090497212647708 -2.3247814459174363e-6 -0.00069490434431432; -0.07185856861268151 -0.792421696456177 0.004184937779847327 -0.09049721264770803 1.2157134723695686 3.3059885334151934e-5 0.011717922601636632; -1.9167789287163796e-6 -2.1624597049020346e-5 1.1617238993773945e-7 -2.3247814459174363e-6 3.3059885334151934e-5 0.0009056135093576957 3.2137612675521565e-7; -0.0006218612683576815 -0.007728195138437067 4.344433216950086e-5 -0.00069490434431432 0.011717922601636633 3.2137612675521565e-7 0.0010220595720602376]
 * x: [-0.533428367773689, 1.4291196455458444, 0.5905388578600534, -0.8797541074382602, -4.59910455905988, -4.605260688347874, -0.6864094300534845]
    20     7.946371e+02     2.425057e+00
 * Current step size: 1.0
 * time: 2218.7000000476837
 * g(x): [2.425057000442717, -0.7115019158760771, -0.014092908030811674, 0.9392287406496003, 0.023200486210294913, 2.3302996788507713e-5, 0.128338102199892]
 * ~inv(H): [0.008739638953229769 0.057812161062153505 -0.0002825408611874522 0.0076106844768564245 -0.09076942703406586 -2.4477990109109806e-6 -0.000833748118306969; 0.05781216106215349 0.9724503133647775 -0.005702182687613206 0.06825839205376108 -1.4533820131795907 -4.0167418006471366e-5 -0.015105686421488861; -0.00028254086118745226 -0.005702182687613205 0.0009413982285071232 -0.0002326154927126499 0.008421835071727467 2.3493655049067646e-7 9.057120435943874e-5; 0.007610684476856426 0.06825839205376107 -0.00023261549271264985 0.01808751389293728 -0.109674013887378 -2.8720800345744838e-6 -0.0009243610781919608; -0.09076942703406587 -1.4533820131795907 0.008421835071727467 -0.10967401388737803 2.180989254469844 6.014438710346041e-5 0.022499242465565627; -2.4477990109109815e-6 -4.016741800647137e-5 2.3493655049067652e-7 -2.8720800345744838e-6 6.014438710346041e-5 0.0009056142692059413 6.237034899303958e-7; -0.0008337481183069692 -0.015105686421488861 9.057120435943874e-5 -0.0009243610781919606 0.022499242465565623 6.237034899303958e-7 0.0011421735383396626]
 * x: [-0.5199618345728998, 1.86609523127762, 0.587933935565521, -0.8486902133123265, -5.245773814186604, -4.6052786138556225, -0.6932690847574483]
    21     7.943858e+02     1.262643e+00
 * Current step size: 1.0
 * time: 2300.702000141144
 * g(x): [1.2626426814293796, -0.3887535360464089, -0.023265375269290303, 0.6415415788634924, 0.009735779009333438, 1.5125918488955201e-5, 0.12906371032823422]
 * ~inv(H): [0.009411968484977884 0.08261618468553363 -0.00044208414482390474 0.008181365406690446 -0.1269084274111342 -3.4638529390766404e-6 -0.0012449644750409574; 0.08261618468553361 1.8848072220201855 -0.011568985400349837 0.08958767669659011 -2.7828563754212254 -7.754127035301704e-5 -0.0302178914742459; -0.0004420841448239048 -0.011568985400349834 0.0009791230457529103 -0.0003699718288289134 0.016970973322439686 4.7526510142375434e-7 0.0001877404769396147; 0.008181365406690448 0.08958767669659008 -0.00036997182882891335 0.01854413716540257 -0.14073148525629187 -3.7457236937939107e-6 -0.0012793237603615495; -0.1269084274111342 -2.782856375421225 0.016970973322439683 -0.1407314852562919 4.118268729662628 0.00011460501782812559 0.04452146992366007; -3.463852939076641e-6 -7.754127035301703e-5 


I am not able to post the complete error. It was around 264 pages in word document.

After running the above code , I got some result which i am posing here.

result
FittedPumasModel

Successful minimization:                      true

Likelihood approximation:              Pumas.FOCEI
Log-likelihood value:                   -793.90411
Number of subjects:                            220
Number of parameters:         Fixed      Optimized
                                  0              5
Observation records:         Active        Missing
    DV:                         220              0
    Total:                      220              0

--------------------
         Estimate
--------------------
tvcl      2.2809
tvv      60.0
tvka      3.7359
ฮฉโ‚,โ‚      0.44204
ฮฉโ‚‚,โ‚‚      0.0
ฮฉโ‚ƒ,โ‚ƒ      0.0097773
ฯƒ         3.84e-7
--------------------

I donโ€™t think i can consider this result. Can you say where i went wrong?

I just looked at your data which I hadnโ€™t done before. You only have a single observation per subject. Thatโ€™s why the standard deviation estimate of the error term is essentially zero. It doesnโ€™t make sense to estimate a model with individual parameters when you only have a single observation per subject.

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what could be the solution ? keep all etaโ€™s ZERO ?

This is more of a modeling philosophy. You should consider using some prior literature information and fix some of your thetaโ€™s and remove some etaโ€™s.

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