Running ‘spelling.R’
  Running ‘testthat.R’ [170s/250s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > if (require("testthat")) {
  +   library(insight)
  + 
  +   if (length(strsplit(packageDescription("insight")$Version, "\\.")[[1]]) > 3) {
  +     Sys.setenv("RunAllinsightTests" = "yes")
  +   } else {
  +     Sys.setenv("RunAllinsightTests" = "no")
  +   }
  + 
  +   osx <- tryCatch(
  +     {
  +       si <- Sys.info()
  +       if (!is.null(si["sysname"])) {
  +         si["sysname"] == "Darwin" || grepl("^darwin", R.version$os)
  +       } else {
  +         FALSE
  +       }
  +     },
  +     error = function(e) {
  +       FALSE
  +     }
  +   )
  + 
  +   if (!osx) {
  +     test_check("insight")
  +   }
  + }
  Loading required package: testthat
  Loading required package: multgee
  Loading required package: gnm
  Loading required package: MCMCglmm
  Loading required package: Matrix
  Loading required package: coda
  Loading required package: ape
  Loading required package: lme4
  Following objects are not identical with m1 (of class "lm"): mtcars ("data.frame")
  Loading required package: aod
  Loading required package: betareg
  Loading required package: blme
  Loading required package: censReg
  Loading required package: maxLik
  Loading required package: miscTools
  
  Please cite the 'maxLik' package as:
  Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.
  
  If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
  https://r-forge.r-project.org/projects/maxlik/
  
  Please cite the 'censReg' package as:
  Henningsen, Arne (2017). censReg: Censored Regression (Tobit) Models. R package version 0.5. http://CRAN.R-Project.org/package=censReg.
  
  If you have questions, suggestions, or comments regarding the 'censReg' package, please use a forum or 'tracker' at the R-Forge site of the 'sampleSelection' project:
  https://r-forge.r-project.org/projects/sampleselection/
  Loading required package: AER
  Loading required package: car
  Loading required package: carData
  Loading required package: lmtest
  Loading required package: zoo
  
  Attaching package: 'zoo'
  
  The following objects are masked from 'package:base':
  
      as.Date, as.Date.numeric
  
  Loading required package: sandwich
  Loading required package: survival
  
  Attaching package: 'survival'
  
  The following object is masked from 'package:aod':
  
      rats
  
  Loading required package: cgam
  Loading required package: coneproj
  Loading required package: svDialogs
  Loading required package: splines
  
  Attaching package: 'cgam'
  
  The following objects are masked from 'package:coneproj':
  
      conc, conv, decr, decr.conc, decr.conv, incr, incr.conc, incr.conv
  
  Loading required package: ordinal
  
  Attaching package: 'ordinal'
  
  The following objects are masked from 'package:lme4':
  
      VarCorr, ranef
  
  Loading required package: MASS
  
  Attaching package: 'MASS'
  
  The following object is masked from 'package:multgee':
  
      housing
  
  Loading required package: nlme
  
  Attaching package: 'nlme'
  
  The following objects are masked from 'package:ordinal':
  
      VarCorr, ranef
  
  The following object is masked from 'package:lme4':
  
      lmList
  
  Loading required package: bdsmatrix
  
  Attaching package: 'bdsmatrix'
  
  The following object is masked from 'package:base':
  
      backsolve
  
  Loading required package: coxme
  
  Attaching package: 'coxme'
  
  The following objects are masked from 'package:ordinal':
  
      VarCorr, ranef
  
  Loading required package: JM
  Loading required package: cplm
  
  Attaching package: 'cplm'
  
  The following object is masked from 'package:coxme':
  
      VarCorr
  
  The following object is masked from 'package:nlme':
  
      VarCorr
  
  The following object is masked from 'package:ordinal':
  
      VarCorr
  
  The following object is masked from 'package:lme4':
  
      VarCorr
  
  Loading required package: crch
  
  Attaching package: 'crch'
  
  The following object is masked from 'package:MCMCglmm':
  
      rtnorm
  
  The following object is masked from 'package:ape':
  
      rtt
  
  Loading required package: quantreg
  Loading required package: SparseM
  
  Attaching package: 'SparseM'
  
  The following object is masked from 'package:bdsmatrix':
  
      backsolve
  
  The following object is masked from 'package:base':
  
      backsolve
  
  
  Attaching package: 'quantreg'
  
  The following object is masked from 'package:survival':
  
      untangle.specials
  
  Loading required package: epiR
  Package epiR 2.0.31 is loaded
  Type help(epi.about) for summary information
  Type browseVignettes(package = 'epiR') to learn how to use epiR for applied epidemiological analyses
  
  
  Loading required package: feisr
  Loading required package: lfe
  
  Attaching package: 'lfe'
  
  The following object is masked from 'package:lmtest':
  
      waldtest
  
  boundary (singular) fit: see ?isSingular
  Loading required package: mgcv
  This is mgcv 1.8-36. For overview type 'help("mgcv-package")'.
  
  Attaching package: 'mgcv'
  
  The following object is masked from 'package:cgam':
  
      s
  
  The following object is masked from 'package:aod':
  
      negbin
  
  Loading required package: gamm4
  This is gamm4 0.2-6
  
  Loading required package: rstanarm
  Loading required package: Rcpp
  This is rstanarm version 2.21.1
  - See https://mc-stan.org/rstanarm/articles/priors for changes to default priors!
  - Default priors may change, so it's safest to specify priors, even if equivalent to the defaults.
  - For execution on a local, multicore CPU with excess RAM we recommend calling
    options(mc.cores = parallel::detectCores())
  
  Attaching package: 'rstanarm'
  
  The following objects are masked from 'package:cplm':
  
      VarCorr, fixef, ranef
  
  The following objects are masked from 'package:ordinal':
  
      VarCorr, ranef
  
  The following object is masked from 'package:car':
  
      logit
  
  The following object is masked from 'package:gnm':
  
      se
  
  Gu & Wahba 4 term additive model
  boundary (singular) fit: see ?isSingular
  Loading required package: fixest
  fixest 0.9.0, BREAKING changes! (Permanently remove this message with fixest_startup_msg(FALSE).) 
  - In i():
      + the first two arguments have been swapped! Now it's i(factor_var, continuous_var) for interactions. 
      + argument 'drop' has been removed (put everything in 'ref' now).
  - In feglm(): 
      + the default family becomes 'gaussian' to be in line with glm(). Hence, for Poisson estimations, please use fepois() instead.
  
  Attaching package: 'fixest'
  
  The following object is masked from 'package:rstanarm':
  
      se
  
  The following object is masked from 'package:cplm':
  
      fixef
  
  The following object is masked from 'package:gnm':
  
      se
  
  Loading required package: gamlss
  Loading required package: gamlss.data
  
  Attaching package: 'gamlss.data'
  
  The following object is masked _by_ '.GlobalEnv':
  
      aids
  
  The following object is masked from 'package:JM':
  
      aids
  
  The following object is masked from 'package:datasets':
  
      sleep
  
  Loading required package: gamlss.dist
  Loading required package: parallel
   **********   GAMLSS Version 5.3-4  ********** 
  For more on GAMLSS look at https://www.gamlss.com/
  Type gamlssNews() to see new features/changes/bug fixes.
  
  
  Attaching package: 'gamlss'
  
  The following object is masked from 'package:lme4':
  
      refit
  
  GAMLSS-RS iteration 1: Global Deviance = 4771.925 
  GAMLSS-CG iteration 1: Global Deviance = 4771.013 
  GAMLSS-CG iteration 2: Global Deviance = 4770.994 
  GAMLSS-CG iteration 3: Global Deviance = 4770.994 
  Loading required package: gee
  Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27
  running glm to get initial regression estimate
  (Intercept)    tensionM    tensionH 
     36.38889   -10.00000   -14.72222 
  Loading required package: geepack
  Loading required package: glmmTMB
  
  Attaching package: 'glmmTMB'
  
  The following object is masked from 'package:gamlss':
  
      refit
  
  The following objects are masked from 'package:cplm':
  
      VarCorr, fixef, ranef
  
  The following objects are masked from 'package:ordinal':
  
      VarCorr, ranef
  
  
   *** caught segfault ***
  address 0, cause 'memory not mapped'
  
  Traceback:
   1: retape(set.defaults = TRUE)
   2: MakeADFun(data.tmb, parameters, map = mapArg, random = randomArg,     profile = NULL, silent = !verbose, DLL = "glmmTMB")
   3: eval(substitute(expr), data, enclos = parent.frame())
   4: eval(substitute(expr), data, enclos = parent.frame())
   5: with.default(TMBStruc, MakeADFun(data.tmb, parameters, map = mapArg,     random = randomArg, profile = NULL, silent = !verbose, DLL = "glmmTMB"))
   6: with(TMBStruc, MakeADFun(data.tmb, parameters, map = mapArg,     random = randomArg, profile = NULL, silent = !verbose, DLL = "glmmTMB"))
   7: fitTMB(TMBStruc)
   8: glmmTMB(count ~ child + camper + (1 | persons), ziformula = ~child +     camper + (1 | persons), data = fish, family = truncated_poisson())
   9: eval(code, test_env)
  10: eval(code, test_env)
  11: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
  12: doTryCatch(return(expr), name, parentenv, handler)
  13: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  14: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  15: doTryCatch(return(expr), name, parentenv, handler)
  16: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  17: tryCatchList(expr, classes, parentenv, handlers)
  18: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  19: test_code(NULL, exprs, env)
  20: source_file(path, child_env(env), wrap = wrap)
  21: FUN(X[[i]], ...)
  22: lapply(test_paths, test_one_file, env = env, wrap = wrap)
  23: force(code)
  24: doWithOneRestart(return(expr), restart)
  25: withOneRestart(expr, restarts[[1L]])
  26: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  27: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, wrap = wrap))
  28: test_files(test_dir = test_dir, test_package = test_package,     test_paths = test_paths, load_helpers = load_helpers, reporter = reporter,     env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package)
  29: test_files(test_dir = path, test_paths = test_paths, test_package = package,     reporter = reporter, load_helpers = load_helpers, env = env,     stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package, parallel = parallel)
  30: test_dir("testthat", package = package, reporter = reporter,     ..., load_package = "installed")
  31: test_check("insight")
  An irrecoverable exception occurred. R is aborting now ...