Running ‘spelling.R’ [0s/1s]
  Running ‘testthat.R’ [149s/234s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/tests.html
  > # * https://testthat.r-lib.org/reference/test_package.html#special-files
  > 
  > library(testthat)
  > library(BayesianMCPMod)
  > 
  > test_check("BayesianMCPMod")
  Loading required package: rstan
  Loading required package: StanHeaders
  
  rstan version 2.32.6 (Stan version 2.32.2)
  
  For execution on a local, multicore CPU with excess RAM we recommend calling
  options(mc.cores = parallel::detectCores()).
  To avoid recompilation of unchanged Stan programs, we recommend calling
  rstan_options(auto_write = TRUE)
  For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,
  change `threads_per_chain` option:
  rstan_options(threads_per_chain = 1)
  
  Loading required package: shiny
  
  Attaching package: 'dplyr'
  
  The following object is masked from 'package:testthat':
  
      matches
  
  The following objects are masked from 'package:stats':
  
      filter, lag
  
  The following objects are masked from 'package:base':
  
      intersect, setdiff, setequal, union
  
  Using default prior reference scale 7.06484551805801
  Using default prior reference scale 7.1096879209905
  Using default prior reference scale 7.1096879209905
  Using default prior reference scale 7.1096879209905
  $Ctr
  Univariate normal mixture
  Reference scale: 9.21011
  Mixture Components:
    comp1        comp2        comp3        robust      
  w   0.23436411   0.22267810   0.04295779   0.50000000
  m -12.18896306 -12.34842538 -12.15357742 -12.25694041
  s   0.94969164   2.19559452   4.11856000   9.30805148
  
  $DG_1
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  $DG_2
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  $DG_3
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  $`Summary of Posterior Distributions`
            mean       sd      2.5%     50.0%    97.5%
  Ctr  -12.25694 6.733262 -27.56803 -12.23615 3.054303
  DG_1 -12.25694 9.308051 -30.50039 -12.25694 5.986505
  DG_2 -12.25694 9.308051 -30.50039 -12.25694 5.986505
  DG_3 -12.25694 9.308051 -30.50039 -12.25694 5.986505
  
  $`Maximum Difference to Control and Dose Group`
  max_diff       DG 
         0        0 
  
  $`Posterior Distributions`
  $`Posterior Distributions`$Ctr
  Univariate normal mixture
  Reference scale: 9.21011
  Mixture Components:
    comp1        comp2        comp3        robust      
  w   0.23436411   0.22267810   0.04295779   0.50000000
  m -12.18896306 -12.34842538 -12.15357742 -12.25694041
  s   0.94969164   2.19559452   4.11856000   9.30805148
  
  $`Posterior Distributions`$DG_1
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  $`Posterior Distributions`$DG_2
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  $`Posterior Distributions`$DG_3
  Univariate normal mixture
  Reference scale: 9.308051
  Mixture Components:
    comp1     
  w   1.000000
  m -12.256940
  s   9.308051
  
  
  Model Coefficients
  linear      e0 = -0.1 delta = -0.1 
  
  Dose Levels
   Ctr = 0 DG_1 = 2.5 
  
  Predictions, Maximum Effect, gAIC, Model Weights & Significance
   Ctr DG_1 mEff gAIC    w 
  -0.1 -0.3  0.2  4.0  1.0 
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 71 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-BMCPMod.R:259:3'): BayesMCPi function works correctly in a simple case ──
  result[["sign"]] (`actual`) not equal to 1 (`expected`).
  
    `actual`: 0
  `expected`: 1
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 71 ]
  Error: Test failures
  Execution halted