R Under development (unstable) (2024-10-09 r87215 ucrt) -- "Unsuffered Consequences"
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> library(testthat)
> library(ChoiceModelR)
> 
> test_check("ChoiceModelR")
                    Logit Data                    
==================================================
Attribute       Type         Levels
-----------------------------------
Attribute 1    Part Worth      5
Attribute 2    Part Worth      3

6 parameters to be estimated.

300 total units.
Average of 4.2 alternatives in each of 49.1 sets per unit.
14726 tasks in total.

Table of choice data pooled across units:
Choice  Count   Pct.
--------------------
   1    3665   24.89%
   2    3633   24.67%
   3    3674   24.95%
   4    2548   17.3%
   5    1206   8.19%

      MCMC Inference for Hierarchical Logit       
==================================================
Total Iterations:          200
Draws used in estimation:  200
Units:                     300
Parameters per unit:       6
Constraints in effect.
Draws are to be saved.
Prior degrees of freedom:  5
Prior variance:            2

MCMC Iteration Beginning...
Iteration  Acceptance   RLH     Pct. Cert.   Avg. Var.   RMS     Time to End
      100  0.376        0.398   0.311        0.56        0.84    0:02  
      200  0.301        0.489   0.475        0.85        1.34    0:00  

Total Time Elapsed: 0:03

Writing estimated unit-level betas to Rbetas.csv in the working directory

Writing RLH, the geometric mean of the likelihood of the choices made,

      across the choice sets of each unit to RLH.csv in the working directory

[1] 0.401353
[1] 0.03316306
                    Logit Data                    
==================================================
Attribute       Type         Levels
-----------------------------------
Attribute 1    Part Worth      5
Attribute 2    Part Worth      3

6 parameters to be estimated.

300 total units.
Average of 5 alternatives in each of 50 sets per unit.
47408 expanded tasks in total.

Table of choice data pooled across units:
Choice  Count   Pct.
--------------------
   1    9362   19.75%
   2    9747   20.56%
   3    6638   14%
   4    10736  22.65%
   5    10925  23.04%

      MCMC Inference for Hierarchical Logit       
==================================================
Total Iterations:          200
Draws used in estimation:  200
Units:                     300
Parameters per unit:       6
Task weight:               5
Constraints in effect.
Draws are to be saved.
Prior degrees of freedom:  5
Prior variance:            2

MCMC Iteration Beginning...
Iteration  Acceptance   RLH     Pct. Cert.   Avg. Var.   RMS     Time to End
      100  0.356        0.344   0.290        0.70        0.93    0:06  
      200  0.304        0.427   0.447        1.03        1.48    0:00  

Total Time Elapsed: 0:12

Writing estimated unit-level betas to Rbetas.csv in the working directory

Writing RLH, the geometric mean of the likelihood of the choices made,

      across the choice sets of each unit to RLH.csv in the working directory

[1] 0.4882356
[1] 0.03988951
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 0 ]
> 
> proc.time()
   user  system elapsed 
  14.95    1.90   16.84