Hi I am trying to fit a very simple model and failing - it might be not enough data, bur I’d love to know if I am doing something wrong.

Model

```
PK = @model begin
@param begin
θ ∈ VectorDomain(6,lower=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0], init=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
# Ω ∈ PSDDomain(5)
# σ_prop ∈ RealDomain(init=0.1)
end
@random begin
η ~ MvNormal(Matrix{Float64}(0.04I, 5, 5))
# η ~ MvNormal(Ω)
end
@pre begin
CL_adc = θ[1]
CLD_adc = θ[2]*exp(η[1])
V1_adc = θ[3]*exp(η[2])
V2_adc = θ[4]*exp(η[3])
Vmax = θ[5]*exp(η[4])
Km = θ[6]*exp(η[5])
end
@init begin
end
@dynamics begin
A1' = -CL_adc*C1 - CLD_adc*(C1-C2) - Vmax*C1/(Km+C1)
A2' = CLD_adc*(C1-C2)
end
@vars begin
C1 := A1/V1_adc
C2 := A2/V2_adc
end
@derived begin
# a1 = A1
Conc_Mean = C1
end
end
```

Params:

```
param = init_param(PK)
```

Data

PKDataMean

|Group|Time|Conc_Mean|

||Any|Float64|Any|

|1|0.1 mg/kg|0.0034722|2.12803|

|2|0.03 mg/kg|0.0034722|0.293033|

|3|0.3 mg/kg|0.0034722|5.51947|

|4|0.1 mg/kg|0.25|1.07887|

|5|0.03 mg/kg|0.25|0.151067|

|6|0.3 mg/kg|0.25|3.18253|

|7|0.1 mg/kg|1.0|0.7315|

|8|0.03 mg/kg|1.0|0.0420333|

|9|0.3 mg/kg|1.0|2.52407|

|10|0.1 mg/kg|2.0|0.4226|

|11|0.03 mg/kg|2.0|missing|

|12|0.3 mg/kg|2.0|2.0864|

|13|0.1 mg/kg|2.99|0.3219|

|14|0.03 mg/kg|2.99|missing|

|15|0.3 mg/kg|2.99|1.3471|

(I also made a table where I remove Group 0.03 mg/kg, in case the problem was caused by missing data)

Filtering if necesary

```
PKDataMean=filter(row -> row.Group ∈ ["0.1 mg/kg", "0.3 mg/kg"], PKDataMean)
```

read_as_Pumas and fit

```
PKdata = read_pumas(PKDataMean, id=:Group, time=:Time, evid=1, dvs=[:Conc_Mean])
res = fit(PK,PKdata,param,Pumas.FOCEI(), solver=Rodas5())
```

ERROR

TypeError: in typeassert, expected ForwardDiff.Dual{ForwardDiff.Tag{getfield(Pumas, Symbol("##145#146")){Float64,Base.Iterators.Pairs{Symbol,Rodas5{0,true,DefaultLinSolve,DataType},Tuple{Symbol},NamedTuple{(:solver,),Tuple{Rodas5{0,true,DefaultLinSolve,DataType}}}},PumasModel{ParamSet{NamedTuple{(:θ,),Tuple{VectorDomain{Array{Float64,1},Array{TransformVariables.Infinity{true},1},Array{Float64,1}}}}},getfield(Main, Symbol("##167#174")),getfield(Main, Symbol("##168#175")),getfield(Main, Symbol("##169#176")),ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,ODEFunction{false,getfield(Main, Symbol("##170#177")),UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},getfield(Main, Symbol("##172#179")),getfield(Main, Symbol("##173#180"))},Subject{NamedTuple{(:Conc_Mean,),Tuple{Array{Union{Missing, Float64},1}}},Nothing,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Int64},1},Array{Float64,1}},NamedTuple{(:θ,),Tuple{Array{Float64,1}}},Pumas.FOCEI,Tuple{}},Float64},Float64,5}, got Float64

if I skip the filtering the error changes to

DimensionMismatch(“vectors must have same length”) -> I assume this is consequence of the missing values.

Thanks and hope this is not to wordy.