Running 'testthat.R' [218s/242s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > Sys.setenv("R_TESTS" = "")
  > 
  > library(testthat)
  > library(rmdcev)
  Loading required package: Rcpp
  This is rmdcev version 1.2.0
  > test_check("rmdcev")
  
  SAMPLING FOR MODEL 'mdcev' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.012171 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 121.71 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
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  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.228772 seconds (Warm-up)
  Chain 1:                0.07619 seconds (Sampling)
  Chain 1:                0.304962 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.01432 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 143.2 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
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  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.110546 seconds (Warm-up)
  Chain 1:                0.156665 seconds (Sampling)
  Chain 1:                0.267211 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.012641 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 126.41 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
  Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
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  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 3.13405 seconds (Warm-up)
  Chain 1:                0.178696 seconds (Sampling)
  Chain 1:                3.31274 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.01587 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 158.7 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
  Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
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  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 6.35911 seconds (Warm-up)
  Chain 1:                0.153705 seconds (Sampling)
  Chain 1:                6.51281 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.016594 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 165.94 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
  Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
  Chain 1: Iteration: 3 / 10 [ 30%]  (Warmup)
  Chain 1: Iteration: 4 / 10 [ 40%]  (Warmup)
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  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
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  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.237159 seconds (Warm-up)
  Chain 1:                0.1154 seconds (Sampling)
  Chain 1:                0.352559 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.00996 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 99.6 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
  Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
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  Chain 1: 
  Chain 1:  Elapsed Time: 0.067469 seconds (Warm-up)
  Chain 1:                0.081512 seconds (Sampling)
  Chain 1:                0.148981 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.009144 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 91.44 seconds.
  Chain 1: Adjust your expectations accordingly!
  Chain 1: 
  Chain 1: 
  Chain 1: WARNING: No variance estimation is
  Chain 1:          performed for num_warmup < 20
  Chain 1: 
  Chain 1: Iteration: 1 / 10 [ 10%]  (Warmup)
  Chain 1: Iteration: 2 / 10 [ 20%]  (Warmup)
  Chain 1: Iteration: 3 / 10 [ 30%]  (Warmup)
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  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.672517 seconds (Warm-up)
  Chain 1:                0.074969 seconds (Sampling)
  Chain 1:                0.747486 seconds (Total)
  Chain 1: 
  [1] -2653.222965
  [1] 5467.626887
  Chain 1: Initial log joint probability = -9825.86
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1: Error evaluating model log probability: Non-finite gradient.
  Error evaluating model log probability: Non-finite gradient.
  Error evaluating model log probability: Non-finite gradient.
  
  Chain 1:       19      -914.527      0.125344       9.75621      0.4281      0.4281       30   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       39      -910.417      0.336908       4.02056           1           1       51   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       59      -908.498      0.186377       1.48621           1           1       73   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       79      -908.224     0.0053696      0.136022           1           1       97   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       99      -908.223     0.0030149     0.0109081           1           1      124   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:      102      -908.223   0.000471434     0.0145965      0.4108           1      128   
  Chain 1: Optimization terminated normally: 
  Chain 1:   Convergence detected: relative gradient magnitude is below tolerance
  [1] "The outside good is not chosen for individuals: 147, -8.73114913702011e-11\n Ensure that the total expenditure on the alternatives is less than income."
  -- 1. Error: Generate alpha MDCEV data (@test-gen_data.R#23)  ------------------
  
  Backtrace:
   1. rmdcev::GenerateMDCEVData(...)
   2. rmdcev::mdcev.data(data, id.var = "id", alt.var = "alt", choice = "quant")
   3. rmdcev:::mdcev.datacheck(data)
  
  Chain 1: Initial log joint probability = -6983.52
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       19      -3953.79     0.0187299       6.56652      0.2878      0.2878       24   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       39      -3953.01    0.00266121       0.30192      0.4447      0.4447       48   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       48      -3953.01    0.00105536     0.0236134           1           1       59   
  Chain 1: Optimization terminated normally: 
  Chain 1:   Convergence detected: relative gradient magnitude is below tolerance
  Chain 1: Initial log joint probability = -3555.46
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       19      -2770.04    0.00295144        2.7883      0.2752      0.2752       26   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       28         -2770   0.000135318     0.0616932      0.4322      0.4322       37   
  Chain 1: Optimization terminated normally: 
  Chain 1:   Convergence detected: relative gradient magnitude is below tolerance
  [1] -2770.001937
  [1] -5073.68569
  NULL
  == testthat results  ===========================================================
  [ OK: 66 | SKIPPED: 0 | WARNINGS: 0 | FAILED: 1 ]
  1. Error: Generate alpha MDCEV data (@test-gen_data.R#23) 
  
  Error: testthat unit tests failed
  Execution halted