CRAN Package Check Results for Package Landmarking

Last updated on 2026-05-11 21:49:48 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.0 9.55 403.17 412.72 OK
r-devel-linux-x86_64-debian-gcc 1.0.0 5.93 291.79 297.72 OK
r-devel-linux-x86_64-fedora-clang 1.0.0 15.00 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.0 15.00 638.46 653.46 OK
r-devel-windows-x86_64 1.0.0 13.00 418.00 431.00 OK
r-patched-linux-x86_64 1.0.0 8.90 383.14 392.04 OK
r-release-linux-x86_64 1.0.0 7.84 380.02 387.86 OK
r-release-macos-arm64 1.0.0 2.00 140.00 142.00 OK
r-release-macos-x86_64 1.0.0 6.00 738.00 744.00 OK
r-release-windows-x86_64 1.0.0 12.00 437.00 449.00 OK
r-oldrel-macos-arm64 1.0.0 OK
r-oldrel-macos-x86_64 1.0.0 6.00 528.00 534.00 OK
r-oldrel-windows-x86_64 1.0.0 14.00 543.00 557.00 OK

Check Details

Version: 1.0.0
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘Landmarking.Rmd’ using rmarkdown --- finished re-building ‘Landmarking.Rmd’ --- re-building ‘how_to_use.Rmd’ using rmarkdown *** caught illegal operation *** address 0x7fdc69597402, cause 'illegal operand' Traceback: 1: nlminb(c(oldPars), function(lmePars) -logLik(lmeSt, lmePars), control = control) 2: lme.formula(fixed = formula_fixed, random = formula_random, data = data_dev_cv, weights = formula_weights, control = lme_control) 3: nlme::lme(fixed = formula_fixed, random = formula_random, data = data_dev_cv, weights = formula_weights, control = lme_control) 4: FUN(X[[i]], ...) 5: lapply(cv_numbers, function(cv_number) { if (length(cv_numbers) > 1) { data_dev_cv <- data_LME_model_dev[data_LME_model_dev[[cv_name]] != cv_number, ] } if (length(cv_numbers) == 1) { data_dev_cv <- data_LME_model_dev } model_LME_cv <- nlme::lme(fixed = formula_fixed, random = formula_random, data = data_dev_cv, weights = formula_weights, control = lme_control) model_LME_cv$call$fixed <- formula_fixed model_LME_cv}) 6: fit_LME_longitudinal(data_long = data_long, x_L = x_l, fixed_effects = fixed_effects, random_effects = random_effects, fixed_effects_time = fixed_effects_time, random_effects_time = random_effects_time, random_slope_in_LME = random_slope_in_LME, random_slope_as_covariate = random_slope_as_covariate, standardise_time = standardise_time, cv_name = cv_name, individual_id = individual_id, lme_control = lme_control) 7: FUN(X[[i]], ...) 8: lapply(1:length(x_L), function(i) { x_l <- x_L[i] x_h <- x_hor[i] data_long <- data_long_x_L[[as.character(x_l)]] print(paste0("Fitting longitudinal submodel, landmark age ", x_l)) data_model_longitudinal <- fit_LME_longitudinal(data_long = data_long, x_L = x_l, fixed_effects = fixed_effects, random_effects = random_effects, fixed_effects_time = fixed_effects_time, random_effects_time = random_effects_time, random_slope_in_LME = random_slope_in_LME, random_slope_as_covariate = random_slope_as_covariate, standardise_time = standardise_time, cv_name = cv_name, individual_id = individual_id, lme_control = lme_control) print(paste0("Complete, landmark age ", x_l)) data_events <- dplyr::distinct(data_long[, c(individual_id, event_status, event_time)]) data_longitudinal <- dplyr::left_join(data_model_longitudinal$data_longitudinal, data_events, by = individual_id) print(paste0("Fitting survival submodel, landmark age ", x_l)) if (random_slope_as_covariate) { random_effects <- c(random_effects, paste0(random_effects, "_slope")) } data_model_survival <- fit_survival_model(data = data_longitudinal, individual_id = individual_id, cv_name = cv_name, covariates = c(fixed_effects, random_effects), event_time = event_time, event_status = event_status, survival_submodel = survival_submodel, x_hor = x_h) print(paste0("Complete, landmark age ", x_l)) prediction_error <- get_model_assessment(data = data_model_survival$data_survival, individual_id = individual_id, event_prediction = "event_prediction", event_status = event_status, event_time = event_time, x_hor = x_h, b = b) list(data = data_model_survival$data_survival, model_longitudinal = data_model_longitudinal$model_longitudinal, model_LME = data_model_longitudinal$model_LME, model_LME_standardise_time = data_model_longitudinal$model_LME_standardise_time, model_survival = data_model_survival$model_survival, prediction_error = prediction_error, call = call)}) 9: fit_LME_landmark(data_long = data_repeat_outcomes[["60"]], x_L = c(60), x_hor = c(65), cross_validation_df = cross_validation_list, fixed_effects = c("ethnicity", "smoking", "diabetes"), fixed_effects_time = "response_time_sbp_stnd", random_effects = c("sbp_stnd", "tchdl_stnd"), random_effects_time = c("response_time_sbp_stnd", "response_time_tchdl_stnd"), individual_id = "id", standardise_time = TRUE, lme_control = nlme::lmeControl(maxIter = 100, msMaxIter = 100), event_time = "event_time", event_status = "event_status", survival_submodel = "cause_specific") 10: eval(expr, envir) 11: eval(expr, envir) 12: withVisible(eval(expr, envir)) 13: withCallingHandlers(code, error = function (e) rlang::entrace(e), message = function (cnd) { watcher$capture_plot_and_output() if (on_message$capture) { watcher$push(cnd) } if (on_message$silence) { invokeRestart("muffleMessage") }}, warning = function (cnd) { if (getOption("warn") >= 2 || getOption("warn") < 0) { return() } watcher$capture_plot_and_output() if (on_warning$capture) { cnd <- sanitize_call(cnd) watcher$push(cnd) } if (on_warning$silence) { invokeRestart("muffleWarning") }}, error = function (cnd) { watcher$capture_plot_and_output() cnd <- sanitize_call(cnd) watcher$push(cnd) switch(on_error, continue = invokeRestart("eval_continue"), stop = invokeRestart("eval_stop"), error = NULL)}) 14: eval(call) 15: eval(call) 16: with_handlers({ for (expr in tle$exprs) { ev <- withVisible(eval(expr, envir)) watcher$capture_plot_and_output() watcher$print_value(ev$value, ev$visible, envir) } TRUE}, handlers) 17: doWithOneRestart(return(expr), restart) 18: withOneRestart(expr, restarts[[1L]]) 19: withRestartList(expr, restarts[-nr]) 20: doWithOneRestart(return(expr), restart) 21: withOneRestart(withRestartList(expr, restarts[-nr]), restarts[[nr]]) 22: withRestartList(expr, restarts) 23: withRestarts(with_handlers({ for (expr in tle$exprs) { ev <- withVisible(eval(expr, envir)) watcher$capture_plot_and_output() watcher$print_value(ev$value, ev$visible, envir) } TRUE}, handlers), eval_continue = function() TRUE, eval_stop = function() FALSE) 24: evaluate::evaluate(...) 25: evaluate(code, envir = env, new_device = FALSE, keep_warning = if (is.numeric(options$warning)) TRUE else options$warning, keep_message = if (is.numeric(options$message)) TRUE else options$message, stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options)) 26: in_dir(input_dir(), expr) 27: in_input_dir(evaluate(code, envir = env, new_device = FALSE, keep_warning = if (is.numeric(options$warning)) TRUE else options$warning, keep_message = if (is.numeric(options$message)) TRUE else options$message, stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options))) 28: eng_r(options) 29: block_exec(params) 30: call_block(x) 31: process_group(group) 32: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { if (progress && is.function(pb$interrupt)) pb$interrupt() if (is_R_CMD_build() || is_R_CMD_check()) error <<- format(e) }) 33: with_options(withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { if (progress && is.function(pb$interrupt)) pb$interrupt() if (is_R_CMD_build() || is_R_CMD_check()) error <<- format(e) }), list(rlang_trace_top_env = knit_global())) 34: xfun:::handle_error(with_options(withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) { if (progress && is.function(pb$interrupt)) pb$interrupt() if (is_R_CMD_build() || is_R_CMD_check()) error <<- format(e) }), list(rlang_trace_top_env = knit_global())), function(loc) { setwd(wd) write_utf8(res, output %n% stdout()) paste0("\nQuitting from ", loc, if (!is.null(error)) paste0("\n", rule(), error, "\n", rule()))}, if (labels[i] != "") sprintf(" [%s]", labels[i]), get_loc) 35: process_file(text, output) 36: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet) 37: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(), output_dir = getwd(), ...) 38: vweave_rmarkdown(...) 39: engine$weave(file, quiet = quiet, encoding = enc) 40: doTryCatch(return(expr), name, parentenv, handler) 41: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 42: tryCatchList(expr, classes, parentenv, handlers) 43: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = "weave", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = "texi2pdf", engine = engine) }}, error = function(e) { OK <<- FALSE message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", file, conditionMessage(e)))}) 44: tools:::.buildOneVignette("how_to_use.Rmd", "/data/gannet/ripley/R/packages/tests-clang/Landmarking.Rcheck/vign_test/Landmarking", TRUE, FALSE, "how_to_use", "UTF-8", "/tmp/RtmpG5dbTF/working_dir/RtmpJ3U4In/file29ceec2e4fb1c6.rds") An irrecoverable exception occurred. R is aborting now ... SUMMARY: processing the following file failed: ‘how_to_use.Rmd’ Error: Vignette re-building failed. Execution halted *** caught segfault *** address 0x1580, cause 'memory not mapped' An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-clang