Running ‘testthat.R’ [205s/220s]
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 0.015104 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 151.04 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.358395 seconds (Warm-up)
  Chain 1:                0.123747 seconds (Sampling)
  Chain 1:                0.482142 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.012621 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 126.21 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.172146 seconds (Warm-up)
  Chain 1:                0.238358 seconds (Sampling)
  Chain 1:                0.410504 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.022006 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 220.06 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 4.32796 seconds (Warm-up)
  Chain 1:                0.153466 seconds (Sampling)
  Chain 1:                4.48142 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.020357 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 203.57 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 8.51938 seconds (Warm-up)
  Chain 1:                0.200326 seconds (Sampling)
  Chain 1:                8.71971 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.019036 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 190.36 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.267107 seconds (Warm-up)
  Chain 1:                0.143782 seconds (Sampling)
  Chain 1:                0.410889 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.020295 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 202.95 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.094628 seconds (Warm-up)
  Chain 1:                0.131108 seconds (Sampling)
  Chain 1:                0.225736 seconds (Total)
  Chain 1: 
  
  SAMPLING FOR MODEL 'mdcev_rp' NOW (CHAIN 1).
  Chain 1: 
  Chain 1: Gradient evaluation took 0.013129 seconds
  Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 131.29 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)
  Chain 1: Iteration: 5 / 10 [ 50%]  (Warmup)
  Chain 1: Iteration: 6 / 10 [ 60%]  (Sampling)
  Chain 1: Iteration: 7 / 10 [ 70%]  (Sampling)
  Chain 1: Iteration: 8 / 10 [ 80%]  (Sampling)
  Chain 1: Iteration: 9 / 10 [ 90%]  (Sampling)
  Chain 1: Iteration: 10 / 10 [100%]  (Sampling)
  Chain 1: 
  Chain 1:  Elapsed Time: 0.879873 seconds (Warm-up)
  Chain 1:                0.076516 seconds (Sampling)
  Chain 1:                0.956389 seconds (Total)
  Chain 1: 
  [1] -2653.222965
  [1] 5467.626887
  Chain 1: Initial log joint probability = -11121.7
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       19      -1416.76      0.698414       20.3845           1           1       29   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       39      -1411.61      0.136014       2.62679           1           1       51   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       59      -1411.22      0.167413       4.21695           1           1       72   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       79      -1411.11     0.0206424      0.180493           1           1       92   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       99      -1411.11   0.000803054     0.0306261           1           1      112   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:      104      -1411.11   0.000790071     0.0222144           1           1      118   
  Chain 1: Optimization terminated normally: 
  Chain 1:   Convergence detected: relative gradient magnitude is below tolerance
  Chain 1: Initial log joint probability = -310.835
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       19      -121.488      0.226622       2.19211           1           1       23   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       39      -121.316    0.00266432      0.086203     0.08421           1       47   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       59      -121.314    0.00790182     0.0227955           1           1       72   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       71      -121.314   0.000608326    0.00133008           1           1       88   
  Chain 1: Optimization terminated normally: 
  Chain 1:   Convergence detected: relative gradient magnitude is below tolerance
  Error in chol.default(-H) : 
    the leading minor of order 6 is not positive definite
  ── 1. Error: Generate alpha MDCEV data (@test-gen_data.R#30)  ──────────────────
  Lapack routine dgesv: system is exactly singular: U[6,6] = 0
  Backtrace:
   1. base::summary(output)
   3. rmdcev:::summary.mdcev(output)
   5. base::solve.default(-object$stan_fit$hessian)
  
  Chain 1: Initial log joint probability = -6414.45
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       19      -3105.82      0.321186       9.99894           1           1       26   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       39      -3104.11    0.00413145      0.745949           1           1       50   
  Chain 1:     Iter      log prob        ||dx||      ||grad||       alpha      alpha0  # evals  Notes 
  Chain 1:       56      -3104.11   0.000565421     0.0730116       0.857       0.857       68   
  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#30) 
  
  Error: testthat unit tests failed
  Execution halted