* using log directory 'd:/Rcompile/CRANpkg/local/4.5/insight.Rcheck' * using R version 4.5.2 (2025-10-31 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 14.3.0 GNU Fortran (GCC) 14.3.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * checking for file 'insight/DESCRIPTION' ... OK * checking extension type ... Package * this is package 'insight' version '1.4.3' * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking whether package 'insight' can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking 'build' directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... 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OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of 'data' directory ... OK * checking data for non-ASCII characters ... [0s] OK * checking data for ASCII and uncompressed saves ... OK * checking installed files from 'inst/doc' ... OK * checking files in 'vignettes' ... OK * checking examples ... [50s] ERROR Running examples in 'insight-Ex.R' failed The error most likely occurred in: > ### Name: is_converged > ### Title: Convergence test for mixed effects models > ### Aliases: is_converged > > ### ** Examples > > ## Don't show: > if (require("lme4", quietly = TRUE)) withAutoprint({ # examplesIf + ## End(Don't show) + library(lme4) + data(cbpp) + set.seed(1) + cbpp$x <- rnorm(nrow(cbpp)) + cbpp$x2 <- runif(nrow(cbpp)) + + model <- glmer( + cbind(incidence, size - incidence) ~ period + x + x2 + (1 + x | herd), + data = cbpp, + family = binomial() + ) + + is_converged(model) + ## Don't show: + }) # examplesIf > library(lme4) > data(cbpp) > set.seed(1) > cbpp$x <- rnorm(nrow(cbpp)) > cbpp$x2 <- runif(nrow(cbpp)) > model <- glmer(cbind(incidence, size - incidence) ~ period + x + x2 + + (1 + x | herd), data = cbpp, family = binomial()) boundary (singular) fit: see help('isSingular') > is_converged(model) Error in h(simpleError(msg, call)) : error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found Calls: withAutoprint ... eval -> eval -> -> .handleSimpleError -> h Execution halted * checking for unstated dependencies in 'tests' ... OK * checking tests ... [169s] ERROR Running 'testthat.R' [168s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(insight) > test_check("insight") Starting 2 test processes. > test-find_transformation.R: boundary (singular) fit: see help('isSingular') > test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 365.2328 > test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 365.1292 > test-gamlss.R: GAMLSS-RS iteration 3: Global Deviance = 365.1269 > test-gamlss.R: GAMLSS-RS iteration 4: Global Deviance = 365.1268 > test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 5779.746 > test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 5779.746 > test-gamlss.R: GAMLSS-RS iteration 1: Global Deviance = 703.1164 > test-gamlss.R: GAMLSS-RS iteration 2: Global Deviance = 703.1164 > test-get_model.R: Loading required namespace: GPArotation > test-get_random.R: boundary (singular) fit: see help('isSingular') > test-glmmPQL.R: iteration 1 Saving _problems/test-is_converged-16.R > test-mmrm.R: mmrm() registered as emmeans extension > test-mmrm.R: mmrm() registered as car::Anova extension > test-model_info.R: boundary (singular) fit: see help('isSingular') > test-nestedLogit.R: list(work = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, > test-nestedLogit.R: 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > test-nestedLogit.R: 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, > test-nestedLogit.R: 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, > test-nestedLogit.R: 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, > test-nestedLogit.R: 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, > test-nestedLogit.R: 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L > test-nestedLogit.R: ), full = c(1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, > test-nestedLogit.R: 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, > test-nestedLogit.R: 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L)) > test-polr.R: > test-polr.R: Re-fitting to get Hessian > test-polr.R: > test-polr.R: > test-polr.R: Re-fitting to get Hessian > test-polr.R: > test-survey_coxph.R: Stratified Independent Sampling design (with replacement) > test-survey_coxph.R: dpbc <- survey::svydesign( > test-survey_coxph.R: id = ~1, > test-survey_coxph.R: prob = ~randprob, > test-survey_coxph.R: strata = ~edema, > test-survey_coxph.R: data = subset(pbc, randomized) > test-survey_coxph.R: ) > test-survey_coxph.R: Stratified Independent Sampling design (with replacement) > test-survey_coxph.R: dpbc <- survey::svydesign( > test-survey_coxph.R: id = ~1, > test-survey_coxph.R: prob = ~randprob, > test-survey_coxph.R: strata = ~edema, > test-survey_coxph.R: data = subset(pbc, randomized) > test-survey_coxph.R: ) > test-survey_coxph.R: Stratified Independent Sampling design (with replacement) > test-survey_coxph.R: dpbc <- survey::svydesign( > test-survey_coxph.R: id = ~1, > test-survey_coxph.R: prob = ~randprob, > test-survey_coxph.R: strata = ~edema, > test-survey_coxph.R: data = subset(pbc, randomized) > test-survey_coxph.R: ) [ FAIL 1 | WARN 4 | SKIP 93 | PASS 3611 ] ══ Skipped tests (93) ══════════════════════════════════════════════════════════ • On CRAN (89): 'test-GLMMadaptive.R:2:1', 'test-averaging.R:1:1', 'test-bias_correction.R:1:1', 'test-betareg.R:197:5', 'test-brms.R:1:1', 'test-brms_aterms.R:1:1', 'test-brms_gr_random_effects.R:1:1', 'test-blmer.R:262:3', 'test-brms_missing.R:1:1', 'test-brms_mm.R:1:1', 'test-brms_von_mises.R:1:1', 'test-clean_names.R:109:3', 'test-clean_parameters.R:1:1', 'test-coxme.R:1:1', 'test-cpglmm.R:152:3', 'test-clmm.R:170:3', 'test-display.R:1:1', 'test-display.R:15:1', 'test-export_table.R:3:1', 'test-export_table.R:7:1', 'test-export_table.R:134:3', 'test-export_table.R:164:3', 'test-export_table.R:193:1', 'test-export_table.R:278:1', 'test-export_table.R:296:3', 'test-export_table.R:328:3', 'test-export_table.R:385:1', 'test-export_table.R:406:3', 'test-export_table.R:470:3', 'test-find_random.R:43:3', 'test-fixest.R:2:1', 'test-find_smooth.R:39:3', 'test-format_table.R:2:1', 'test-format_table_ci.R:72:1', 'test-gam.R:2:1', 'test-get_data.R:507:1', 'test-get_loglikelihood.R:143:3', 'test-get_loglikelihood.R:223:3', 'test-get_predicted.R:2:1', 'test-get_priors.R:1:1', 'test-get_varcov.R:43:3', 'test-get_varcov.R:57:3', 'test-get_datagrid.R:1068:3', 'test-get_datagrid.R:1105:5', 'test-is_converged.R:32:1', 'test-iv_robust.R:120:3', 'test-lavaan.R:1:1', 'test-lcmm.R:1:1', 'test-lme.R:28:3', 'test-lme.R:212:3', 'test-glmmTMB.R:67:3', 'test-glmmTMB.R:767:3', 'test-glmmTMB.R:803:3', 'test-glmmTMB.R:1142:3', 'test-marginaleffects.R:1:1', 'test-mgcv.R:1:1', 'test-mipo.R:1:1', 'test-mlogit.R:1:1', 'test-model_info.R:106:3', 'test-modelbased.R:1:1', 'test-mvrstanarm.R:1:1', 'test-null_model.R:85:3', 'test-panelr-asym.R:165:3', 'test-panelr.R:295:3', 'test-phylolm.R:1:1', 'test-print_parameters.R:1:1', 'test-r2_nakagawa_bernoulli.R:1:1', 'test-r2_nakagawa_beta.R:1:1', 'test-r2_nakagawa_binomial.R:1:1', 'test-r2_nakagawa_gamma.R:1:1', 'test-r2_nakagawa_linear.R:1:1', 'test-r2_nakagawa_negbin.R:1:1', 'test-r2_nakagawa_negbin_zi.R:1:1', 'test-r2_nakagawa_ordered_beta.R:1:1', 'test-r2_nakagawa_poisson.R:1:1', 'test-r2_nakagawa_poisson_zi.R:1:1', 'test-r2_nakagawa_truncated_poisson.R:1:1', 'test-r2_nakagawa_tweedie.R:1:1', 'test-rlmer.R:276:3', 'test-rms.R:1:1', 'test-rqss.R:1:1', 'test-rstanarm.R:1:1', 'test-sdmTMB.R:1:1', 'test-selection.R:2:1', 'test-spatial.R:2:1', 'test-svylme.R:1:1', 'test-tidymodels.R:1:1', 'test-vgam.R:2:1', 'test-weightit.R:1:1' • Package `logistf` is loaded and breaks `mmrm::mmrm()` (1): 'test-mmrm.R:4:1' • works interactively (2): 'test-coxph-panel.R:34:3', 'test-coxph.R:38:3' • {bigglm} is not installed (1): 'test-model_info.R:24:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-is_converged.R:16:3'): is_converged ──────────────────────────── Error in `h(simpleError(msg, call))`: error in evaluating the argument 'a' in selecting a method for function 'solve': object 'Hessian' not found Backtrace: ▆ 1. ├─testthat::expect_true(is_converged(model)) at test-is_converged.R:16:3 2. │ └─testthat::quasi_label(enquo(object), label) 3. │ └─rlang::eval_bare(expr, quo_get_env(quo)) 4. ├─insight::is_converged(model) 5. ├─insight:::is_converged.merMod(model) 6. │ ├─base::with(x@optinfo$derivs, Matrix::solve(Hessian, gradient)) 7. │ ├─base::with.default(x@optinfo$derivs, Matrix::solve(Hessian, gradient)) 8. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame()) 9. │ │ └─base::eval(substitute(expr), data, enclos = parent.frame()) 10. │ └─Matrix::solve(Hessian, gradient) 11. └─base::.handleSimpleError(...) 12. └─base (local) h(simpleError(msg, call)) [ FAIL 1 | WARN 4 | SKIP 93 | PASS 3611 ] Error: ! Test failures. Execution halted * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... [14s] OK * checking PDF version of manual ... [26s] OK * checking HTML version of manual ... [27s] OK * DONE Status: 2 ERRORs