Running ‘testthat.R’ [68s/93s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(psycho)
  > 
  > test_check("psycho")
  Failed with error:  'there is no package called 'GPArotation''
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  Rejecting initial value:
    Log probability evaluates to log(0), i.e. negative infinity.
    Stan can't start sampling from this initial value.
  
  Gradient evaluation took 5.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.422275 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000135 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.35 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 2.08873 seconds (Warm-up)
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                 3.77559 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 5.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.51 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.05724 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.43 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.057417 seconds (Warm-up)
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                 0.113567 seconds (Total)
  
  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
  Gradient evaluation took 8.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.84 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
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  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100     -4e+02             1.000            1.000
     200     -2e+02             1.011            1.021
     300     -2e+02             0.682            1.000
     400     -2e+02             0.511            1.000
     500     -2e+02             0.409            0.024
     600     -2e+02             0.341            0.024
     700     -2e+02             0.293            0.002   MEDIAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  ------------------------------------------------------------
  EXPERIMENTAL ALGORITHM:
    This procedure has not been thoroughly tested and may be unstable
    or buggy. The interface is subject to change.
  ------------------------------------------------------------
  
  
  
  Gradient evaluation took 8.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.81 seconds.
  Adjust your expectations accordingly!
  
  
  Begin eta adaptation.
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  Success! Found best value [eta = 1] earlier than expected.
  
  Begin stochastic gradient ascent.
    iter       ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
     100     -9e+04             1.000            1.000
     200     -6e+02            79.074          157.147
     300     -5e+02            52.759            1.000
     400     -2e+02            39.982            1.651
     500     -2e+02            31.989            1.000
     600     -2e+02            26.660            1.000
     700     -2e+02            22.854            0.130
     800     -2e+02            19.999            0.130
     900     -2e+02            17.778            0.018
    1000     -2e+02            16.000            0.018
    1100     -2e+02            15.902            0.016   MAY BE DIVERGING... INSPECT ELBO
    1200     -2e+02             0.188            0.014
    1300     -2e+02             0.176            0.014
    1400     -2e+02             0.011            0.014
    1500     -2e+02             0.010            0.013   MEAN ELBO CONVERGED
  
  Drawing a sample of size 1000 from the approximate posterior... 
  COMPLETED.
  Initial log joint probability = -100816
  Optimization terminated normally: 
    Convergence detected: relative gradient magnitude is below tolerance
  The Crawford-Howell (1998) t-test suggests no dissociation between test X and test Y (t(5) = 2.10, p = 0.09<b0>). The patient's score on test X is not significantly altered compared to its score on test Y.
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 0.000228 seconds
  1000 transitions using 10 leapfrog steps per transition would take 2.28 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.738636 seconds (Warm-up)
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                 1.455 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 9.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.92 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.675508 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.000112 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.12 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.665385 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 0.000183 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.83 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.680503 seconds (Warm-up)
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                 1.38906 seconds (Total)
  
  ── 1. Error: If it works. (@test-get_contrasts.stanreg.R#10)  ──────────────────
  number of items to replace is not a multiple of replacement length
  1: psycho::get_contrasts(fit, "Salary") at testthat/test-get_contrasts.stanreg.R:10
  2: get_contrasts.stanreg(fit, "Salary")
  3: fit %>% emmeans::emmeans(formula) %>% coda::as.mcmc() %>% as.matrix() %>% coda::as.mcmc() %>% 
         as.data.frame()
  4: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
  5: eval(quote(`_fseq`(`_lhs`)), env, env)
  6: eval(quote(`_fseq`(`_lhs`)), env, env)
  7: `_fseq`(`_lhs`)
  8: freduce(value, `_function_list`)
  9: function_list[[i]](value)
  10: as.matrix(.)
  11: as.matrix.mcmc(.)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1).
  
  Gradient evaluation took 5.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.52 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.137624 seconds (Warm-up)
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                 0.280281 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2).
  
  Gradient evaluation took 3.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.37 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.137311 seconds (Warm-up)
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                 0.297184 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3).
  
  Gradient evaluation took 5.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.51 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.128669 seconds (Warm-up)
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                 0.255475 seconds (Total)
  
  
  SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4).
  
  Gradient evaluation took 3.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.128443 seconds (Warm-up)
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                 0.258744 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 4.9e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.49 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.09827 seconds (Warm-up)
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                 0.195244 seconds (Total)
  
  
  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 2.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.27 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.102077 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 4.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.097948 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 2.7e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.27 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.115846 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.74 seconds.
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   Elapsed Time: 0.296817 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 4.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.303183 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 6.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.68 seconds.
  Adjust your expectations accordingly!
  
  
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   Elapsed Time: 0.283314 seconds (Warm-up)
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 5.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.51 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 0.000135 seconds
  1000 transitions using 10 leapfrog steps per transition would take 1.35 seconds.
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.78 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
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           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 3.3e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.33 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 3.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.38 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 3.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.35 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 7.5e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.75 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 5.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.54 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 5.2e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.52 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 6.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.61 seconds.
  Adjust your expectations accordingly!
  
  
  WARNING: There aren't enough warmup iterations to fit the
           three stages of adaptation as currently configured.
           Reducing each adaptation stage to 15%/75%/10% of
           the given number of warmup iterations:
             init_buffer = 7
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             term_buffer = 5
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
  
  Gradient evaluation took 6.8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.68 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
  
  Gradient evaluation took 4.1e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.41 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
  
  Gradient evaluation took 8e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.8 seconds.
  Adjust your expectations accordingly!
  
  
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  SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
  
  Gradient evaluation took 3.4e-05 seconds
  1000 transitions using 10 leapfrog steps per transition would take 0.34 seconds.
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  .0%
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  .100%
  1
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 140 SKIPPED: 0 FAILED: 1
  1. Error: If it works. (@test-get_contrasts.stanreg.R#10) 
  
  Error: testthat unit tests failed
  Execution halted