# How to exhibit results of SIR or bootstrap properly like in table

**URL:** <https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452>\
**Category:** Diagnostics\
**Created:** [January 18, 2021, 1:45am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452 "2021-01-18T01:45:28Z")\
**Posts on this page:** 16\
**Page:** 1

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 18, 2021, 1:45am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/1 "2021-01-18T01:45:28Z")

</div>

The SIR could be performed with model and sampling/resampling number, BUT I am quite confused about the data structure of the results and thus don’t know how to read it.

Besides, could there be an default/recommended settings for bootstrap/SIR process? (From a completely new user of Julia)

---

<div class="post-metadata">

**Author:** ![vijay](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/vijay/32/96_2.png) [@vijay](https://discourse.pumas.ai/u/vijay)\
**Post date:** [January 19, 2021, 1:55am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/2 "2021-01-19T01:55:32Z")

</div>

hi @diabloyg , welcome to the community!

you develop SIR() using this syntax

```julia
my_sir = infer(my_fit, Pumas.SIR(samples=200))

```

you can then get the results of this using the standard `coeftable` function

```julia
coeftable(my_sir)

```

> Besides, could there be an default/recommended settings for bootstrap/SIR process? (From a completely new user of Julia)

There is a major update to the documentation happening that should be released in a day or two and i will point you to the exact location of all the options.

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 6:52am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/3 "2021-01-19T06:52:41Z")

</div>

@vijay Thanks very much for your reply.

However, when I tried to test my model in another laptop with weaker-performance CPU (AMD Ryzen 7 PRO 3700 U), there are many mistakes during the FOCEI estimation, which didn’t happen in computer with Intel i7 10850.

I wonder is there any difference for Pumas between AMD and Intel. I tried to collect information but have no idea about this.

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [January 19, 2021, 7:06am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/4 "2021-01-19T07:06:53Z")

</div>

> [@diabloyg](#):
>
> there are many mistakes during the FOCEI estimation

Please share the exact errors and warnings that you see as well as the command that you ran. Otherwise, it’s not possible to know what is going on. There shouldn’t be a difference between AMD and Intel so it might be a good idea to check that the two programs are indeed identical.

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 7:27am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/6 "2021-01-19T07:27:37Z")

</div>

> [@andreasnoack](#):
>
> Please share the exact errors and warnings that you see as well as the command that you ran. Otherwise, it’s not possible to know what is going on. There shouldn’t be a difference between AMD and Intel so it might be a good idea to check that the two programs are indeed identical.

Generally the mistakes were as follows:

```julia
Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ DiffEqBase C:\Users\julia.julia\packages\DiffEqBase\3iigH\src\integrator_interface.jl:343
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ DiffEqBase C:\Users\julia.julia\packages\DiffEqBase\3iigH\src\integrator_interface.jl:343

```

I have copyed the file to the laptop so it should exactly the same. In another Intel platform I successfully get the model and performed SIR. The codes are there:

```julia
using CSV, Pumas, Plots, Random, JLD2

dataset = DataFrame!(CSV.File(
“./P1PK_20200907.csv”,
missingstrings = ["", “.”, “NA”, “BQL”],
))

popdata = read_pumas(
dataset,
observations = [:dv],
covariates = [:bw, :age, :sexx, :racex, :alb],
event_data = true,
)

mymodel = @model begin
@param begin
tv_cl ∈ RealDomain(lower = 0.001, upper = 200, init = 40)
tv_vc ∈ RealDomain(lower = 0.001, upper = 10000, init = 5000)
tv_vp ∈ RealDomain(lower = 0.001, upper = 5000, init = 3000)
tv_cld ∈ RealDomain(lower = 0.001, upper = 100, init = 30)
tv_vmax ∈ RealDomain(lower = 0.001, upper = 1000000, init = 200000)
tv_km ∈ RealDomain(lower = 0.001, upper = 1000, init = 400)
tv_bw_cl ∈ RealDomain(lower = 0.001, upper = 3, init = 1.5)
tv_bw_vc ∈ RealDomain(lower = 0.001, upper = 3, init = 1)
omega ∈ PDiagDomain(init = [0.1, 0.1, 0.1, 0.1])
epsprop ∈ RealDomain(lower = 0.0001, init = 0.1)
end
@random begin
eta ~ MvNormal(omega)
end
@covariates bw
@pre begin
bw_cl = tv_bw_cl
bw_vc = tv_bw_vc
cl = tv_cl * (bw / 65)^tv_bw_cl * exp(eta[1])
vc = tv_vc * (bw / 65)^tv_bw_vc * exp(eta[2])
vp = tv_vp * exp(eta[3])
cld = tv_cld * exp(eta[4])
vmax = tv_vmax
km = tv_km
end
@init begin
central = 0
peripheral = 0
end
@vars begin
conc = central / vc
k12 = cld / vc
k21 = cld / vp
ke = cl / vc
end
@dynamics begin
central’ =
-ke * central - k12 * central + k21 * peripheral -
vmax * conc / (km + conc)
peripheral’ = k12 * central - k21 * peripheral
end
@derived begin
dv ~ @. Normal(conc, sqrt(conc * epsprop)^2)
end
end

param = init_param(mymodel)

result = fit(mymodel, popdata, param, Pumas.MAP(Pumas.FOCEI()))

```

Additionally, when I tried to load the saved results from previouly running, it told me:

```julia
┌ Warning: some parameters could not be resolved for type ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238
┌ Warning: some parameters could not be resolved for type Pumas.FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46},Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc,
:omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}; reading as Pumas.FittedPumasModel{PumasModel,Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1234
┌ Warning: some parameters could not be resolved for type PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238

```

The load process is okey in the computer that I ran the model.

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 7:35am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/7 "2021-01-19T07:35:32Z")

</div>

@andreasnoack  
Since the saved model cannot be load in my AMD laptop, and the exactly same model cannot be fitted, I believe it’s not due to model code itself but something others.

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [January 19, 2021, 8:24am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/8 "2021-01-19T08:24:26Z")

</div>

> [@diabloyg](#):
>
> Additionally, when I tried to load the saved results from previouly running, it told me:

Please include the code that you use for saving and loading as well.

Are you using the same version of Julia and Pumas? What’s the output from `versioninfo()` and `] st` on the two machines?

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 10:04am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/9 "2021-01-19T10:04:25Z")

</div>

Continuing the discussion from [How to exhibit results of SIR or bootstrap properly like in table](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/8):

> [@andreasnoack](#):
>
> `versioninfo()`

For versioninfo() information:

Julia Version 1.5.2  
Commit 539f3ce943 (2020-09-23 23:17 UTC)  
Platform Info:  
OS: Windows (x86\_64-w64-mingw32)  
CPU: AMD Ryzen 7 PRO 3700U w/ Radeon Vega Mobile Gfx  
WORD\_SIZE: 64  
LIBM: libopenlibm  
LLVM: libLLVM-9.0.1 (ORCJIT, znver1)  
Environment:  
JULIA\_DEPOT\_PATH = C:\Users\gyang.julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia  
JULIA\_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a  
JULIA\_LOAD\_PATH = C:\Users\gyang.julia\environments\JuliaPro\_v1.5.2-2;C:\Users\gyang.julia\Pumas;@;@v#.#;@stdlib  
JULIA\_NUM\_THREADS = 8  
JULIA\_PKG\_SERVER = [pkg.juliahub.com](http://pkg.juliahub.com)

I think they are the same since they are from one setup packages.

For saving and loading code:

detail = infer(result)

wres = wresiduals(result)

resout = DataFrame(inspect(result))

@save “test2.jld2” result detail wres resout

@load “test2.jld2” result detail wres resout

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [January 19, 2021, 10:21am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/10 "2021-01-19T10:21:18Z")

</div>

Please also share the output from `] st` and please share the same info from the other machine. There might be small relevant differences so we shouldn’t assume that they are identical.

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 2:44pm UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/11 "2021-01-19T14:44:47Z")

</div>

From my view there is no much difference. For the laptop in which estimation cannot run correctly:

] st

Status `C:\Users\gyang\.julia\environments\JuliaPro_v1.5.2-2\Project.toml`  
[c3fe647b] AbstractAlgebra v0.11.1 ⚲  
[621f4979] AbstractFFTs v0.5.0 ⚲  
[80f14c24] AbstractMCMC v2.1.0 ⚲  
[1520ce14] AbstractTrees v0.3.3 ⚲  
[79e6a3ab] Adapt v2.3.0 ⚲  
[0bf59076] AdvancedHMC v0.2.26 ⚲  
[dce04be8] ArgCheck v1.1.0 ⚲  
[ec485272] ArnoldiMethod v0.0.4 ⚲  
[7d9fca2a] Arpack v0.4.0 ⚲  
[68821587] Arpack\_jll v3.5.0+3 ⚲  
[4fba245c] ArrayInterface v2.13.7 ⚲  
[4c555306] ArrayLayouts v0.3.8 ⚲  
[69666777] Arrow v0.4.1 ⚲  
[56f22d72] Artifacts v1.3.0 ⚲  
[bf4720bc] AssetRegistry v0.1.0 ⚲  
[c52e3926] Atom v0.12.21 ⚲  
[6710c13c] AutoGrad v1.2.3 ⚲  
[15f4f7f2] AutoHashEquals v0.2.0 ⚲  
[13072b0f] AxisAlgorithms v1.0.0 ⚲  
[39de3d68] AxisArrays v0.4.3 ⚲  
[ab4f0b2a] BFloat16s v0.1.0 ⚲  
[aae01518] BandedMatrices v0.15.15 ⚲  
[198e06fe] BangBang v0.3.29 ⚲  
[6e4b80f9] BenchmarkTools v0.5.0 ⚲  
[b99e7846] BinaryProvider v0.5.10 ⚲  
[4ece37e6] Bioequivalence v0.1.9 ⚲  
[8e7c35d0] BlockArrays v0.12.11 ⚲  
[764a87c0] BoundaryValueDiffEq v2.5.0 ⚲  
[e1450e63] BufferedStreams v1.0.0 ⚲  
[4f18b42c] BusinessDays v0.9.11 ⚲  
[6e34b625] Bzip2\_jll v1.0.6+5 ⚲  
[fa961155] CEnum v0.4.1 ⚲  
[70588ee8] CSSUtil v0.1.1 ⚲  
[00ebfdb7] CSTParser v2.5.0 ⚲  
[336ed68f] CSV v0.7.7 ⚲  
[052768ef] CUDA v2.1.0 ⚲  
[83423d85] Cairo\_jll v1.16.0+6 ⚲  
[49dc2e85] Calculus v0.5.1 ⚲  
[a603d957] CanonicalTraits v0.2.3 ⚲  
[aafaddc9] CatIndices v0.2.1 ⚲  
[324d7699] CategoricalArrays v0.8.3 ⚲  
[082447d4] ChainRules v0.7.32 ⚲  
[d360d2e6] ChainRulesCore v0.9.17 ⚲  
[cdddcdb0] ChainRulesTestUtils v0.5.3 ⚲  
[34f1f09b] ClusterManagers v0.3.2 ⚲  
[aaaa29a8] Clustering v0.14.2 ⚲  
[53a63b46] CodeTools v0.7.1 ⚲  
[da1fd8a2] CodeTracking v0.5.12 ⚲  
[523fee87] CodecBzip2 v0.7.2 ⚲  
[5ba52731] CodecLz4 v0.4.0 ⚲  
[944b1d66] CodecZlib v0.7.0 ⚲  
[6b39b394] CodecZstd v0.7.0 ⚲  
[35d6a980] ColorSchemes v3.10.1 ⚲  
[3da002f7] ColorTypes v0.10.9 ⚲  
[c3611d14] ColorVectorSpace v0.8.6 ⚲  
[5ae59095] Colors v0.12.4 ⚲  
[861a8166] Combinatorics v1.0.2 ⚲  
[a80b9123] CommonMark v0.6.4 ⚲  
[38540f10] CommonSolve v0.2.0 ⚲  
[bbf7d656] CommonSubexpressions v0.3.0 ⚲  
[34da2185] Compat v3.23.0 ⚲  
[e66e0078] CompilerSupportLibraries\_jll v0.3.4+0 ⚲  
[a33af91c] CompositionsBase v0.1.0 ⚲  
[ed09eef8] ComputationalResources v0.3.2 ⚲  
[8f4d0f93] Conda v1.5.0 ⚲  
[88cd18e8] ConsoleProgressMonitor v0.1.2 ⚲  
[187b0558] ConstructionBase v1.0.0 ⚲  
[d38c429a] Contour v0.5.5 ⚲  
[150eb455] CoordinateTransformations v0.6.0 ⚲  
[adafc99b] CpuId v0.2.2 ⚲  
[a8cc5b0e] Crayons v4.0.4 ⚲  
[dc8bdbbb] CustomUnitRanges v1.0.0 ⚲  
[717857b8] DSP v0.6.8 ⚲  
[9a962f9c] DataAPI v1.4.0 ⚲  
[a93c6f00] DataFrames v0.21.8 ⚲  
[1313f7d8] DataFramesMeta v0.5.1 ⚲  
[82cc6244] DataInterpolations v3.2.1 ⚲  
[864edb3b] DataStructures v0.18.8 ⚲  
[e2d170a0] DataValueInterfaces v1.0.0 ⚲  
[e7dc6d0d] DataValues v0.4.13 ⚲  
[31a5f54b] Debugger v0.6.6 ⚲  
[7806a523] DecisionTree v0.10.10 ⚲  
[244e2a9f] DefineSingletons v0.1.0 ⚲  
[bcd4f6db] DelayDiffEq v5.25.1 ⚲  
[2b5f629d] DiffEqBase v6.48.2 ⚲  
[459566f4] DiffEqCallbacks v2.14.1 ⚲  
[01453d9d] DiffEqDiffTools v1.7.0 ⚲  
[5a0ffddc] DiffEqFinancial v2.4.0 ⚲  
[c894b116] DiffEqJump v6.10.1 ⚲  
[77a26b50] DiffEqNoiseProcess v5.4.0 ⚲  
[055956cb] DiffEqPhysics v3.6.0 ⚲  
[41bf760c] DiffEqSensitivity v6.33.0 ⚲  
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[ade2ca70] Dates ⚲  
[8bb1440f] DelimitedFiles ⚲  
[8ba89e20] Distributed ⚲  
[7b1f6079] FileWatching ⚲  
[9fa8497b] Future ⚲  
[b77e0a4c] InteractiveUtils ⚲  
[76f85450] LibGit2 ⚲  
[8f399da3] Libdl ⚲  
[37e2e46d] LinearAlgebra ⚲  
[56ddb016] Logging ⚲  
[d6f4376e] Markdown ⚲  
[a63ad114] Mmap ⚲  
[44cfe95a] Pkg ⚲  
[de0858da] Printf ⚲  
[9abbd945] Profile ⚲  
[3fa0cd96] REPL ⚲  
[9a3f8284] Random ⚲  
[ea8e919c] SHA ⚲  
[9e88b42a] Serialization ⚲  
[1a1011a3] SharedArrays ⚲  
[6462fe0b] Sockets ⚲  
[2f01184e] SparseArrays ⚲  
[10745b16] Statistics ⚲  
[4607b0f0] SuiteSparse ⚲  
[8dfed614] Test ⚲  
[cf7118a7] UUIDs ⚲  
[4ec0a83e] Unicode ⚲

versioninfo()

Julia Version 1.5.2  
Commit 539f3ce943 (2020-09-23 23:17 UTC)  
Platform Info:  
OS: Windows (x86\_64-w64-mingw32)  
CPU: AMD Ryzen 7 PRO 3700U w/ Radeon Vega Mobile Gfx  
WORD\_SIZE: 64  
LIBM: libopenlibm  
LLVM: libLLVM-9.0.1 (ORCJIT, znver1)  
Environment:  
JULIA\_DEPOT\_PATH = C:\Users\gyang.julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia  
JULIA\_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a  
JULIA\_LOAD\_PATH = C:\Users\gyang.julia\environments\JuliaPro\_v1.5.2-2;C:\Users\gyang.julia\Pumas;@;@v#.#;@stdlib  
JULIA\_NUM\_THREADS = 8  
JULIA\_PKG\_SERVER = [pkg.juliahub.com](http://pkg.juliahub.com)

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 2:45pm UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/12 "2021-01-19T14:45:20Z")

</div>

For the computer in which the code runs normally:

Status `C:\Users\admin\.julia\environments\JuliaPro_v1.5.2-2\Project.toml`  
[c3fe647b] AbstractAlgebra v0.11.1 ⚲  
[621f4979] AbstractFFTs v0.5.0 ⚲  
[80f14c24] AbstractMCMC v2.1.0 ⚲  
[1520ce14] AbstractTrees v0.3.3 ⚲  
[79e6a3ab] Adapt v2.3.0 ⚲  
[0bf59076] AdvancedHMC v0.2.26 ⚲  
[dce04be8] ArgCheck v1.1.0 ⚲  
[ec485272] ArnoldiMethod v0.0.4 ⚲  
[7d9fca2a] Arpack v0.4.0 ⚲  
[68821587] Arpack\_jll v3.5.0+3 ⚲  
[4fba245c] ArrayInterface v2.13.7 ⚲  
[4c555306] ArrayLayouts v0.3.8 ⚲  
[69666777] Arrow v0.4.1 ⚲  
[56f22d72] Artifacts v1.3.0 ⚲  
[bf4720bc] AssetRegistry v0.1.0 ⚲  
[c52e3926] Atom v0.12.21 ⚲  
[6710c13c] AutoGrad v1.2.3 ⚲  
[15f4f7f2] AutoHashEquals v0.2.0 ⚲  
[13072b0f] AxisAlgorithms v1.0.0 ⚲  
[39de3d68] AxisArrays v0.4.3 ⚲  
[ab4f0b2a] BFloat16s v0.1.0 ⚲  
[aae01518] BandedMatrices v0.15.15 ⚲  
[198e06fe] BangBang v0.3.29 ⚲  
[6e4b80f9] BenchmarkTools v0.5.0 ⚲  
[b99e7846] BinaryProvider v0.5.10 ⚲  
[4ece37e6] Bioequivalence v0.1.9 ⚲  
[8e7c35d0] BlockArrays v0.12.11 ⚲  
[764a87c0] BoundaryValueDiffEq v2.5.0 ⚲  
[e1450e63] BufferedStreams v1.0.0 ⚲  
[4f18b42c] BusinessDays v0.9.11 ⚲  
[6e34b625] Bzip2\_jll v1.0.6+5 ⚲  
[fa961155] CEnum v0.4.1 ⚲  
[70588ee8] CSSUtil v0.1.1 ⚲  
[00ebfdb7] CSTParser v2.5.0 ⚲  
[336ed68f] CSV v0.7.7 ⚲  
[052768ef] CUDA v2.1.0 ⚲  
[83423d85] Cairo\_jll v1.16.0+6 ⚲  
[49dc2e85] Calculus v0.5.1 ⚲  
[a603d957] CanonicalTraits v0.2.3 ⚲  
[aafaddc9] CatIndices v0.2.1 ⚲  
[324d7699] CategoricalArrays v0.8.3 ⚲  
[082447d4] ChainRules v0.7.32 ⚲  
[d360d2e6] ChainRulesCore v0.9.17 ⚲  
[cdddcdb0] ChainRulesTestUtils v0.5.3 ⚲  
[34f1f09b] ClusterManagers v0.3.2 ⚲  
[aaaa29a8] Clustering v0.14.2 ⚲  
[53a63b46] CodeTools v0.7.1 ⚲  
[da1fd8a2] CodeTracking v0.5.12 ⚲  
[523fee87] CodecBzip2 v0.7.2 ⚲  
[5ba52731] CodecLz4 v0.4.0 ⚲  
[944b1d66] CodecZlib v0.7.0 ⚲  
[6b39b394] CodecZstd v0.7.0 ⚲  
[35d6a980] ColorSchemes v3.10.1 ⚲  
[3da002f7] ColorTypes v0.10.9 ⚲  
[c3611d14] ColorVectorSpace v0.8.6 ⚲  
[5ae59095] Colors v0.12.4 ⚲  
[861a8166] Combinatorics v1.0.2 ⚲  
[a80b9123] CommonMark v0.6.4 ⚲  
[38540f10] CommonSolve v0.2.0 ⚲  
[bbf7d656] CommonSubexpressions v0.3.0 ⚲  
[34da2185] Compat v3.23.0 ⚲  
[e66e0078] CompilerSupportLibraries\_jll v0.3.4+0 ⚲  
[a33af91c] CompositionsBase v0.1.0 ⚲  
[ed09eef8] ComputationalResources v0.3.2 ⚲  
[8f4d0f93] Conda v1.5.0 ⚲  
[88cd18e8] ConsoleProgressMonitor v0.1.2 ⚲  
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[d38c429a] Contour v0.5.5 ⚲  
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[adafc99b] CpuId v0.2.2 ⚲  
[a8cc5b0e] Crayons v4.0.4 ⚲  
[dc8bdbbb] CustomUnitRanges v1.0.0 ⚲  
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[1313f7d8] DataFramesMeta v0.5.1 ⚲  
[82cc6244] DataInterpolations v3.2.1 ⚲  
[864edb3b] DataStructures v0.18.8 ⚲  
[e2d170a0] DataValueInterfaces v1.0.0 ⚲  
[e7dc6d0d] DataValues v0.4.13 ⚲  
[31a5f54b] Debugger v0.6.6 ⚲  
[7806a523] DecisionTree v0.10.10 ⚲  
[244e2a9f] DefineSingletons v0.1.0 ⚲  
[bcd4f6db] DelayDiffEq v5.25.1 ⚲  
[2b5f629d] DiffEqBase v6.48.2 ⚲  
[459566f4] DiffEqCallbacks v2.14.1 ⚲  
[01453d9d] DiffEqDiffTools v1.7.0 ⚲  
[5a0ffddc] DiffEqFinancial v2.4.0 ⚲  
[c894b116] DiffEqJump v6.10.1 ⚲  
[77a26b50] DiffEqNoiseProcess v5.4.0 ⚲  
[055956cb] DiffEqPhysics v3.6.0 ⚲  
[41bf760c] DiffEqSensitivity v6.33.0 ⚲  
[163ba53b] DiffResults v1.0.2 ⚲  
[b552c78f] DiffRules v1.0.1 ⚲  
[0c46a032] DifferentialEquations v6.15.0 ⚲  
[c619ae07] DimensionalPlotRecipes v1.2.0 ⚲  
[b4f34e82] Distances v0.9.2 ⚲  
[31c24e10] Distributions v0.23.2 ⚲  
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[f5851436] FFTW\_jll v3.3.9+6 ⚲  
[9aa1b823] FastClosures v0.3.2 ⚲  
[5789e2e9] FileIO v1.4.4 ⚲  
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[6a86dc24] FiniteDiff v2.7.1 ⚲  
[26cc04aa] FiniteDifferences v0.11.2 ⚲  
[53c48c17] FixedPointNumbers v0.8.4 ⚲  
[08572546] FlameGraphs v0.2.4 ⚲  
[587475ba] Flux v0.11.2 ⚲  
[a3f928ae] Fontconfig\_jll v2.13.1+14 ⚲  
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[f6369f11] ForwardDiff v0.10.12 ⚲  
[d7e528f0] FreeType2\_jll v2.10.1+5 ⚲  
[559328eb] FriBidi\_jll v1.0.5+6 ⚲  
[069b7b12] FunctionWrappers v1.1.1 ⚲  
[de31a74c] FunctionalCollections v0.5.0 ⚲  
[d9f16b24] Functors v0.1.0 ⚲  
[fb4132e2] FuzzyCompletions v0.2.4 ⚲  
[0656b61e] GLFW\_jll v3.3.2+1 ⚲  
[38e38edf] GLM v1.3.11 ⚲  
[781609d7] GMP\_jll v6.1.2+6 ⚲  
[0c68f7d7] GPUArrays v6.1.1 ⚲  
[61eb1bfa] GPUCompiler v0.8.3 ⚲  
[28b8d3ca] GR v0.53.0 ⚲  
[d2c73de3] GR\_jll v0.52.0+0 ⚲  
[6b9d7cbe] GeneralizedGenerated v0.2.8 ⚲  
[01680d73] GenericSVD v0.3.0 ⚲  
[5c1252a2] GeometryBasics v0.3.3 ⚲  
[78b55507] Gettext\_jll v0.20.1+7 ⚲  
[7746bdde] Glib\_jll v2.59.0+4 ⚲  
[a2bd30eb] Graphics v1.0.2 ⚲  
[42e2da0e] Grisu v1.0.0 ⚲  
[19dc6840] HCubature v1.4.0 ⚲  
[cd3eb016] HTTP v0.8.19 ⚲  
[9fb69e20] Hiccup v0.2.2 ⚲  
[eafb193a] Highlights v0.4.5 ⚲  
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[b5f81e59] IOCapture v0.1.1 ⚲  
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[bbac6d45] IdentityRanges v0.3.1 ⚲  
[615f187c] IfElse v0.1.0 ⚲  
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[a09fc81d] ImageCore v0.8.18 ⚲  
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[6a3955dd] ImageFiltering v0.6.17 ⚲  
[6218d12a] ImageMagick v1.1.6 ⚲  
[c73af94c] ImageMagick\_jll v6.9.10-12+3 ⚲  
[bc367c6b] ImageMetadata v0.9.4 ⚲  
[787d08f9] ImageMorphology v0.2.9 ⚲  
[2996bd0c] ImageQualityIndexes v0.2.0 ⚲  
[4e3cecfd] ImageShow v0.2.3 ⚲  
[02fcd773] ImageTransformations v0.8.6 ⚲  
[916415d5] Images v0.23.1 ⚲  
[9b13fd28] IndirectArrays v0.5.1 ⚲  
[d25df0c9] Inflate v0.1.2 ⚲  
[83e8ac13] IniFile v0.5.0 ⚲  
[22cec73e] InitialValues v0.2.10 ⚲  
[505f98c9] InplaceOps v0.3.0 ⚲  
[1d5cc7b8] IntelOpenMP\_jll v2018.0.3+0 ⚲  
[c601a237] Interact v0.10.3 ⚲  
[d3863d7c] InteractBase v0.10.5 ⚲  
[a98d9a8b] Interpolations v0.12.10 ⚲  
[8197267c] IntervalSets v0.5.1 ⚲  
[d8418881] Intervals v1.5.0 ⚲  
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[c8e1da08] IterTools v1.3.0 ⚲  
[42fd0dbc] IterativeSolvers v0.8.4 ⚲  
[82899510] IteratorInterfaceExtensions v1.0.0 ⚲  
[6042db11] JDBC v0.5.0 ⚲  
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[692b3bcd] JLLWrappers v1.1.3 ⚲  
[97c1335a] JSExpr v0.5.2 ⚲  
[682c06a0] JSON v0.21.1 ⚲  
[7d188eb4] JSONSchema v0.3.2 ⚲  
[494afd89] JavaCall v0.7.6 ⚲  
[aacddb02] JpegTurbo\_jll v2.0.1+3 ⚲  
[4076af6c] JuMP v0.21.5 ⚲  
[98e50ef6] JuliaFormatter v0.7.6 ⚲  
[aa1ae85d] JuliaInterpreter v0.7.26 ⚲  
[ea4eb333] JuliaRunClient v0.2.2 ⚲  
[b14d175d] JuliaVariables v0.2.3 ⚲  
[480116ec] JuliaWebAPI v0.6.2 ⚲  
[e5e0dc1b] Juno v0.8.4 ⚲  
[5ab0869b] KernelDensity v0.6.2 ⚲  
[1902f260] Knet v1.4.3 ⚲  
[bcebb21b] Knockout v0.2.4 ⚲  
[c1c5ebd0] LAME\_jll v3.100.0+3 ⚲  
[929cbde3] LLVM v3.3.0 ⚲  
[7c4cb9fa] LNR v0.2.1 ⚲  
[dd4b983a] LZO\_jll v2.10.0+3 ⚲  
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[e9f186c6] Libffi\_jll v3.2.1+4 ⚲  
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[7e76a0d4] Libglvnd\_jll v1.3.0+3 ⚲  
[7add5ba3] Libgpg\_error\_jll v1.36.0+3 ⚲  
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[5ced341a] Lz4\_jll v1.9.2+2 ⚲  
[c7f686f2] MCMCChains v4.2.4 ⚲  
[d00139f3] METIS\_jll v5.1.0+5 ⚲  
[856f044c] MKL\_jll v2020.2.254+0 ⚲  
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[4c82536e] Nettle\_jll v3.4.1+2 ⚲  
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[458c3c95] OpenSSL\_jll v1.1.1+6 ⚲  
[efe28fd5] OpenSpecFun\_jll v0.5.3+4 ⚲  
[429524aa] Optim v0.22.0 ⚲  
[91d4177d] Opus\_jll v1.3.1+3 ⚲  
[bac558e1] OrderedCollections v1.3.2 ⚲  
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[2f80f16e] PCRE\_jll v8.42.0+4 ⚲  
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[65888b18] ParameterizedFunctions v5.6.0 ⚲  
[d96e819e] Parameters v0.12.1 ⚲  
[fae87a5f] ParserCombinator v2.0.0 ⚲  
[69de0a69] Parsers v1.0.12 ⚲  
[fa939f87] Pidfile v1.2.0 ⚲  
[b98c9c47] Pipe v1.3.0 ⚲  
[30392449] Pixman\_jll v0.38.4+5 ⚲  
[4722fa14] PkgAuthentication v0.3.0 ⚲  
[ccf2f8ad] PlotThemes v2.0.0 ⚲  
[995b91a9] PlotUtils v1.0.7 ⚲  
[91a5bcdd] Plots v1.8.1 ⚲  
[e409e4f3] PoissonRandom v0.4.0 ⚲  
[f27b6e38] Polynomials v1.1.11 ⚲  
[2dfb63ee] PooledArrays v0.5.3 ⚲  
[85a6dd25] PositiveFactorizations v0.2.3 ⚲  
[8162dcfd] PrettyPrint v0.2.0 ⚲  
[08abe8d2] PrettyTables v0.9.1 ⚲  
[27ebfcd6] Primes v0.5.0 ⚲  
[33c8b6b6] ProgressLogging v0.1.3 ⚲  
[92933f4c] ProgressMeter v1.4.0 ⚲  
[3349acd9] ProtoBuf v0.9.0 ⚲  
[4f2c3c20] Pumas v1.1.0 ⚲  
[0c61e9cd] PumasPlots v0.2.0 ⚲  
[b7b41870] PumasTutorials v0.1.1 ⚲  
[438e738f] PyCall v1.92.1 ⚲  
[d330b81b] PyPlot v2.9.0 ⚲  
[784f63db] Qhull\_jll v2019.1.0+2 ⚲  
[ede63266] Qt\_jll v5.15.0+3 ⚲  
[1fd47b50] QuadGK v2.4.1 ⚲  
[67601950] Quadrature v1.5.0 ⚲  
[fcd29c91] QuantEcon v0.16.2 ⚲  
[c6596682] QuantileRegressions v0.1.5 ⚲  
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[2913bbd2] StatsBase v0.33.2 ⚲  
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[88034a9c] StringDistances v0.8.0 ⚲  
[09ab397b] StructArrays v0.4.4 ⚲  
[856f2bd8] StructTypes v1.1.0 ⚲  
[bea87d4a] SuiteSparse\_jll v5.4.0+9 ⚲  
[c3572dad] Sundials v4.3.0 ⚲  
[fb77eaff] Sundials\_jll v5.2.0+1 ⚲  
[7522ee7d] SweepOperator v0.3.0 ⚲  
[24249f21] SymPy v1.0.32 ⚲  
[d1185830] SymbolicUtils v0.5.2 ⚲  
[ab02a1b2] TableOperations v0.3.0 ⚲  
[3783bdb8] TableTraits v1.0.0 ⚲  
[40c74d1a] TableView v0.6.1 ⚲  
[bd369af6] Tables v1.2.1 ⚲  
[5d786b92] TerminalLoggers v0.1.2 ⚲  
[ac1d9e8a] ThreadsX v0.1.7 ⚲  
[06e1c1a7] TiledIteration v0.2.5 ⚲  
[f269a46b] TimeZones v1.5.0 ⚲  
[a759f4b9] TimerOutputs v0.5.7 ⚲  
[0796e94c] Tokenize v0.5.8 ⚲  
[9f7883ad] Tracker v0.2.12 ⚲  
[3bb67fe8] TranscodingStreams v0.9.5 ⚲  
[28d57a85] Transducers v0.4.53 ⚲  
[84d833dd] TransformVariables v0.3.4 ⚲  
[a2a6695c] TreeViews v0.3.0 ⚲  
[30578b45] URIParser v0.4.1 ⚲  
[3a884ed6] UnPack v1.0.2 ⚲  
[b8865327] UnicodePlots v1.3.0 ⚲  
[1986cc42] Unitful v1.5.0 ⚲  
[3d5dd08c] VectorizationBase v0.12.33 ⚲  
[81def892] VersionParsing v1.2.0 ⚲  
[19fa3120] VertexSafeGraphs v0.1.2 ⚲  
[a2964d1f] Wayland\_jll v1.17.0+4 ⚲  
[2381bf8a] Wayland\_protocols\_jll v1.18.0+4 ⚲  
[44d3d7a6] Weave v0.10.6 ⚲  
[0f1e0344] WebIO v0.8.93 ⚲  
[104b5d7c] WebSockets v1.5.2 ⚲  
[cc8bc4a8] Widgets v0.6.2 ⚲  
[1b915085] WinReg v0.3.1 ⚲  
[efce3f68] WoodburyMatrices v0.5.3 ⚲  
[02c8fc9c] XML2\_jll v2.9.10+3 ⚲  
[aed1982a] XSLT\_jll v1.1.33+4 ⚲  
[4f6342f7] Xorg\_libX11\_jll v1.6.9+4 ⚲  
[0c0b7dd1] Xorg\_libXau\_jll v1.0.9+4 ⚲  
[935fb764] Xorg\_libXcursor\_jll v1.2.0+4 ⚲  
[a3789734] Xorg\_libXdmcp\_jll v1.1.3+4 ⚲  
[1082639a] Xorg\_libXext\_jll v1.3.4+4 ⚲  
[d091e8ba] Xorg\_libXfixes\_jll v5.0.3+4 ⚲  
[a51aa0fd] Xorg\_libXi\_jll v1.7.10+4 ⚲  
[d1454406] Xorg\_libXinerama\_jll v1.1.4+4 ⚲  
[ec84b674] Xorg\_libXrandr\_jll v1.5.2+4 ⚲  
[ea2f1a96] Xorg\_libXrender\_jll v0.9.10+4 ⚲  
[14d82f49] Xorg\_libpthread\_stubs\_jll v0.1.0+3 ⚲  
[c7cfdc94] Xorg\_libxcb\_jll v1.13.0+3 ⚲  
[cc61e674] Xorg\_libxkbfile\_jll v1.1.0+4 ⚲  
[12413925] Xorg\_xcb\_util\_image\_jll v0.4.0+0 ⚲  
[2def613f] Xorg\_xcb\_util\_jll v0.4.0+0 ⚲  
[975044d2] Xorg\_xcb\_util\_keysyms\_jll v0.4.0+0 ⚲  
[0d47668e] Xorg\_xcb\_util\_renderutil\_jll v0.3.9+0 ⚲  
[c22f9ab0] Xorg\_xcb\_util\_wm\_jll v0.4.1+0 ⚲  
[35661453] Xorg\_xkbcomp\_jll v1.4.2+4 ⚲  
[33bec58e] Xorg\_xkeyboard\_config\_jll v2.27.0+4 ⚲  
[c5fb5394] Xorg\_xtrans\_jll v1.4.0+3 ⚲  
[ddb6d928] YAML v0.4.2 ⚲  
[c2297ded] ZMQ v1.2.1 ⚲  
[8f1865be] ZeroMQ\_jll v4.3.2+5 ⚲  
[a5390f91] ZipFile v0.9.3 ⚲  
[83775a58] Zlib\_jll v1.2.11+18 ⚲  
[3161d3a3] Zstd\_jll v1.4.5+2 ⚲  
[e88e6eb3] Zygote v0.5.9 ⚲  
[700de1a5] ZygoteRules v0.2.0 ⚲  
[0ac62f75] libass\_jll v0.14.0+4 ⚲  
[f638f0a6] libfdk\_aac\_jll v0.1.6+4 ⚲  
[b53b4c65] libpng\_jll v1.6.37+6 ⚲  
[f27f6e37] libvorbis\_jll v1.3.6+6 ⚲  
[1270edf5] x264\_jll v2020.7.14+2 ⚲  
[dfaa095f] x265\_jll v3.0.0+3 ⚲  
[d8fb68d0] xkbcommon\_jll v0.9.1+5 ⚲  
[2a0f44e3] Base64 ⚲  
[ade2ca70] Dates ⚲  
[8bb1440f] DelimitedFiles ⚲  
[8ba89e20] Distributed ⚲  
[7b1f6079] FileWatching ⚲  
[9fa8497b] Future ⚲  
[b77e0a4c] InteractiveUtils ⚲  
[76f85450] LibGit2 ⚲  
[8f399da3] Libdl ⚲  
[37e2e46d] LinearAlgebra ⚲  
[56ddb016] Logging ⚲  
[d6f4376e] Markdown ⚲  
[a63ad114] Mmap ⚲  
[44cfe95a] Pkg ⚲  
[de0858da] Printf ⚲  
[9abbd945] Profile ⚲  
[3fa0cd96] REPL ⚲  
[9a3f8284] Random ⚲  
[ea8e919c] SHA ⚲  
[9e88b42a] Serialization ⚲  
[1a1011a3] SharedArrays ⚲  
[6462fe0b] Sockets ⚲  
[2f01184e] SparseArrays ⚲  
[10745b16] Statistics ⚲  
[4607b0f0] SuiteSparse ⚲  
[8dfed614] Test ⚲  
[cf7118a7] UUIDs ⚲  
[4ec0a83e] Unicode ⚲

Julia Version 1.5.2  
Commit 539f3ce943 (2020-09-23 23:17 UTC)  
Platform Info:  
OS: Windows (x86\_64-w64-mingw32)  
CPU: Intel® Core™ i7-10875H CPU @ 2.30GHz  
WORD\_SIZE: 64  
LIBM: libopenlibm  
LLVM: libLLVM-9.0.1 (ORCJIT, skylake)  
Environment:  
JULIA\_DEPOT\_PATH = C:\Users\admin.julia;D:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;D:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia  
JULIA\_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a  
JULIA\_LOAD\_PATH = C:\Users\admin.julia\environments\JuliaPro\_v1.5.2-2;C:\Users\admin.julia\Pumas;@;@v#.#;@stdlib  
JULIA\_NUM\_THREADS = 8  
JULIA\_PKG\_SERVER = [pkg.juliahub.com](http://pkg.juliahub.com)

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [January 19, 2021, 3:24pm UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/13 "2021-01-19T15:24:58Z")

</div>

Did you run `using Pumas` before you ran `@load “test2.jld2” result detail wres resout`?

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 19, 2021, 4:17pm UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/14 "2021-01-19T16:17:40Z")

</div>

Yes I did. The first line was " using CSV, Pumas, Plots, Random, JLD2".

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 25, 2021, 3:15am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/15 "2021-01-25T03:15:31Z")

</div>

Hi @andreasnoack. I further confirmed that, within once opening of atom, the @load function is ok. However, if I opened the atom for another time, the @load function is invalid even in the same computer. Does this mean that the JLD2 is not compatible with pumas? I also tried other I/O approaches but none of them worked. There are always these message:

Warning: some parameters could not be resolved for type ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}; reconstructing  
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238  
┌ Warning: some parameters could not be resolved for type Pumas.FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:tv\_cl, :tv\_vc, :tv\_vp, :tv\_cld, :tv\_vmax, :tv\_km, :tv\_bw\_cl, :tv\_bw\_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46},Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize\_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show\_trace, :store\_trace, :extended\_trace, :g\_tol, :allow\_f\_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv\_cl, :tv\_vc, :tv\_vp, :tv\_cld, :tv\_vmax, :tv\_km, :tv\_bw\_cl, :tv\_bw\_vc,  
:omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}; reading as Pumas.FittedPumasModel{PumasModel,Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize\_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show\_trace, :store\_trace, :extended\_trace, :g\_tol, :allow\_f\_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv\_cl, :tv\_vc, :tv\_vp, :tv\_cld, :tv\_vmax, :tv\_km, :tv\_bw\_cl, :tv\_bw\_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}  
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1234  
┌ Warning: some parameters could not be resolved for type PumasModel{ParamSet{NamedTuple{(:tv\_cl, :tv\_vc, :tv\_vp, :tv\_cld, :tv\_vmax, :tv\_km, :tv\_bw\_cl, :tv\_bw\_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46}; reconstructing  
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238

```auto

```

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [January 25, 2021, 9:03am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/16 "2021-01-25T09:03:25Z")

</div>

We have debugged your issues a little further.

1. It seems that `JLD2` isn’t able to handle our models so I’ll recommend using `Serialization` instead, i.e. something like

```auto
julia> open("saved_model.jls", "w") do f
         serialize(f, Dict("fit" => _fit, "infer" => _infer))
       end

```

and then

```auto
julia> d = deserialize("saved_model.jls")
Dict{String,Any} with 2 entries:
  "fit" => FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:θ, :Ω, :Σ),Tuple{VectorDomain{Array{Flo…
  "infer" => FittedPumasModelInference{FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:θ, :Ω, :Σ),Tu…

```

1. It looks like there might be some issues with ODE solving on AMD systems but we are still debugging this issues. We’ll let you know once we have a better understanding of the issue.

---

<div class="post-metadata">

**Author:** ![diabloyg](https://avatars.discourse-cdn.com/v4/letter/d/ee59a6/32.png) [@diabloyg](https://discourse.pumas.ai/u/diabloyg)\
**Post date:** [January 25, 2021, 10:49am UTC](https://discourse.pumas.ai/t/how-to-exhibit-results-of-sir-or-bootstrap-properly-like-in-table/452/17 "2021-01-25T10:49:30Z")

</div>

Thanks for your reply.

For the first question, the Serialization worked. However, after I typed " d = deserialize(“saved\_model.jls”)" there, the ‘d’ was actually a dictionary object (I suppose, I’m new to programming language), but not a PumasModel, FittedPumasModel object or something produced/to be fitted by Pumas.

Nontheless, those stored/needed objects could be accessed through the dict index such as:

mymodel = d[“index name”].

Which is quite convenient to store all information of a model into one file. Thanks for your recommendation.