Running ‘testthat.R’ [22s/30s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library("testthat")
  > library("blavaan")
  Loading required package: lavaan
  This is lavaan 0.6-7
  lavaan is BETA software! Please report any bugs.
  Loading required package: Rcpp
  Loading required package: RcppParallel
  
  Attaching package: 'RcppParallel'
  
  The following object is masked from 'package:Rcpp':
  
      LdFlags
  
  This is blavaan 0.3-12
  On multicore systems, we suggest use of future::plan("multiprocess") for faster post-MCMC computations.
  > 
  > test_check("blavaan")
  blavaan NOTE: Arguments ov.cp and lv.cp are deprecated. Use cp instead. 
  
  blavaan NOTE: fa priors are not available with stan. srs priors will be used. 
  Compiling rjags model...
  Calling the simulation using the rjags method...
  Adapting the model for 1 iterations...
  Burning in the model for 1 iterations...
  Running the model for 3 iterations...
  Simulation complete
  Calculating summary statistics...
  Note: The monitored variables 'psi[2,2,1]', 'psi[3,3,1]',
  'alpha[2,1,1]' and 'alpha[3,1,1]' appear to be non-stochastic; they
  will not be included in the convergence diagnostic
  Calculating the Gelman-Rubin statistic for 8 variables....
  Note: Unable to calculate the multivariate psrf
  Finished running the simulation
  Computing posterior predictives...
  [1] "Error in as(from, \"lgCMatrix\") : \n  no method or default for coercing \"ldiMatrix\" to \"lgCMatrix\"\n"
  attr(,"class")
  [1] "try-error"
  attr(,"condition")
  <simpleError in as(from, "lgCMatrix"): no method or default for coercing "ldiMatrix" to "lgCMatrix">
  ══ Warnings ════════════════════════════════════════════════════════════════════
  ── Warning (???): blavaan arguments ────────────────────────────────────────────
  The adaptation phase of the model was not completed in 1 iterations, so the current samples may not be optimal - try increasing the number of iterations to the "adapt" argument
  Backtrace:
    1. blavaan::blavaan(...)
    8. runjags::run.jags(...)
    9. runjags::extend.jags(...)
   10. runjags:::runjags.start(...)
  ── Warning (???): blavaan arguments ────────────────────────────────────────────
  blavaan WARNING: at least one parameter has a psrf > 1.2.
  Backtrace:
   1. blavaan::blavaan(...)
  ── Warning (???): blavaan arguments ────────────────────────────────────────────
  blavaan WARNING: Small effective sample sizes (< 100) for some parameters.
  Backtrace:
   1. blavaan::blavaan(...)
  ── Warning (tests.blavaanobject-methods.R:31:5): blavaan object methods work ───
  
  1 (1.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstan))) tests.blavaanobject-methods.R:31:4
    5. blavaan:::fitMeasures(fitjags)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::waic.matrix(casells)
   10. loo:::throw_pwaic_warnings(pointwise[, "p_waic"], digits = 1)
   11. loo:::.warn(msg)
  ── Warning (tests.blavaanobject-methods.R:31:5): blavaan object methods work ───
  Some Pareto k diagnostic values are too high. See help('pareto-k-diagnostic') for details.
  
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstan))) tests.blavaanobject-methods.R:31:4
    5. blavaan:::fitMeasures(fitjags)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::loo.matrix(casells, r_eff = ref)
   10. loo:::importance_sampling.matrix(...)
   11. loo:::do_importance_sampling(...)
   12. loo:::throw_pareto_warnings(pareto_k)
   13. loo:::.warn(...)
  ── Warning (tests.blavaanobject-methods.R:31:5): blavaan object methods work ───
  
  1 (1.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstan))) tests.blavaanobject-methods.R:31:4
    5. blavaan:::fitMeasures(fitstan)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::waic.matrix(casells)
   10. loo:::throw_pwaic_warnings(pointwise[, "p_waic"], digits = 1)
   11. loo:::.warn(msg)
  ── Warning (tests.blavaanobject-methods.R:31:5): blavaan object methods work ───
  Some Pareto k diagnostic values are too high. See help('pareto-k-diagnostic') for details.
  
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstan))) tests.blavaanobject-methods.R:31:4
    5. blavaan:::fitMeasures(fitstan)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::loo.matrix(casells, r_eff = ref)
   10. loo:::importance_sampling.matrix(...)
   11. loo:::do_importance_sampling(...)
   12. loo:::throw_pareto_warnings(pareto_k)
   13. loo:::.warn(...)
  ── Warning (tests.blavaanobject-methods.R:33:5): blavaan object methods work ───
  
  1 (1.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstanc))) tests.blavaanobject-methods.R:33:4
    5. blavaan:::fitMeasures(fitjags)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::waic.matrix(casells)
   10. loo:::throw_pwaic_warnings(pointwise[, "p_waic"], digits = 1)
   11. loo:::.warn(msg)
  ── Warning (tests.blavaanobject-methods.R:33:5): blavaan object methods work ───
  Some Pareto k diagnostic values are too high. See help('pareto-k-diagnostic') for details.
  
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstanc))) tests.blavaanobject-methods.R:33:4
    5. blavaan:::fitMeasures(fitjags)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::loo.matrix(casells, r_eff = ref)
   10. loo:::importance_sampling.matrix(...)
   11. loo:::do_importance_sampling(...)
   12. loo:::throw_pareto_warnings(pareto_k)
   13. loo:::.warn(...)
  ── Warning (tests.blavaanobject-methods.R:33:5): blavaan object methods work ───
  
  3 (3.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstanc))) tests.blavaanobject-methods.R:33:4
    5. blavaan:::fitMeasures(fitstanc)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::waic.matrix(casells)
   10. loo:::throw_pwaic_warnings(pointwise[, "p_waic"], digits = 1)
   11. loo:::.warn(msg)
  ── Warning (tests.blavaanobject-methods.R:33:5): blavaan object methods work ───
  Some Pareto k diagnostic values are too high. See help('pareto-k-diagnostic') for details.
  
  Backtrace:
    1. testthat::expect_equal(length(fitMeasures(fitjags)), length(fitMeasures(fitstanc))) tests.blavaanobject-methods.R:33:4
    5. blavaan:::fitMeasures(fitstanc)
    6. blavaan:::.local(object, fit.measures, baseline.model, ...)
    7. blavaan:::blav_fit_measures(...)
    9. loo::loo.matrix(casells, r_eff = ref)
   10. loo:::importance_sampling.matrix(...)
   11. loo:::do_importance_sampling(...)
   12. loo:::throw_pareto_warnings(pareto_k)
   13. loo:::.warn(...)
  ── Warning (tests.blavaanobject-methods.R:126:3): blavaan object methods work ──
  
  1 (1.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
  Backtrace:
   1. blavaan::blavFitIndices(fitstan) tests.blavaanobject-methods.R:126:2
   3. blavaan:::fitMeasures(object, paste0("p_", pD))
   4. blavaan:::.local(object, fit.measures, baseline.model, ...)
   5. blavaan:::blav_fit_measures(...)
   7. loo::waic.matrix(casells)
   8. loo:::throw_pwaic_warnings(pointwise[, "p_waic"], digits = 1)
   9. loo:::.warn(msg)
  ── Warning (tests.blavaanobject-methods.R:126:3): blavaan object methods work ──
  Some Pareto k diagnostic values are too high. See help('pareto-k-diagnostic') for details.
  
  Backtrace:
    1. blavaan::blavFitIndices(fitstan) tests.blavaanobject-methods.R:126:2
    3. blavaan:::fitMeasures(object, paste0("p_", pD))
    4. blavaan:::.local(object, fit.measures, baseline.model, ...)
    5. blavaan:::blav_fit_measures(...)
    7. loo::loo.matrix(casells, r_eff = ref)
    8. loo:::importance_sampling.matrix(...)
    9. loo:::do_importance_sampling(...)
   10. loo:::throw_pareto_warnings(pareto_k)
   11. loo:::.warn(...)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error (???): blavaan arguments ──────────────────────────────────────────────
  Error: blavaan ERROR: problem with translation from lavaan to MCMC syntax.
  Backtrace:
      █
   1. └─blavaan::blavaan(...)
  
  [ FAIL 1 | WARN 13 | SKIP 0 | PASS 61 ]
  Error: Test failures
  Execution halted