CRAN Package Check Results for Maintainer ‘Lukas Baumann <baumann at imbi.uni-heidelberg.de>’

Last updated on 2026-04-17 11:54:18 CEST.

Package	ERROR	NOTE	OK
baskexact		2	12
basksim	3		11
blindrecalc			14
findn			14

Package baskexact

Current CRAN status: NOTE: 2, OK: 12

Version: 1.0.1
Check: dependencies in R code
Result: NOTE Namespace in Imports field not imported from: ‘ggplot2’ All declared Imports should be used. Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Package basksim

Current CRAN status: ERROR: 3, OK: 11

Version: 2.1.0
Check: tests
Result: ERROR Running ‘testthat.R’ [103s/115s] 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(basksim) > > test_check("basksim") Saving _problems/test-adjust_lambda-64.R Saving _problems/test-get_details-126.R [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] ══ Skipped tests (13) ══════════════════════════════════════════════════════════ • On CRAN (13): 'test-adjust_lambda.R:15:3', 'test-adjust_lambda.R:119:3', 'test-get_details.R:11:3', 'test-get_details.R:35:3', 'test-get_details.R:203:3', 'test-get_details.R:234:5', 'test-get_details.R:297:3', 'test-get_details.R:335:3', 'test-get_details.R:383:3', 'test-get_details.R:420:3', 'test-get_details.R:460:3', 'test-get_details.R:486:3', 'test-opt_design.R:19:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-adjust_lambda.R:63:3'): adjust_lambda works for exnex ────────── Error in `(function (mu_mean, mu_sd, tau_scale, mu_j = NULL, tau_j = NULL, w_j, w_nex = NULL, mean_nex = NULL, sd_nex = NULL) { error_mu_mean <- "Providing a numeric for the argument 'mu_mean'" error_mu_sd <- "Providing a positive numeric for the argument 'mu_sd'" error_tau_scale <- "Providing a positive numeric for the argument 'tau_scale'" error_mu_j <- "Providing a (vector of) numeric(s) for the argument 'mu_j'" error_tau_j <- "Providing a (vector of) positive numeric(s) for the argument 'tau_j'" error_w_j <- "Providing a numeric in (0, 1) for the argument 'w_j'" error_w_nex <- "Providing a numeric vector of weights in [0, 1] summing to 1 for the argument 'w_nex'" error_mean_nex <- "Providing a numeric matrix for the argument 'mean_nex'" error_sd_nex <- "Providing a positive numeric matrix for the argument 'sd_nex'" error_dim <- "'mean_nex' and 'sd_nex' must have the same dimensions, and nrow(mean_nex) must equal length(w_nex)" error_mu_mean_sd <- "'mu_mean' and 'mu_sd' must have same length" error_mu_j_tau_j <- "'mu_j' and 'tau_j' must have the same length" error_w_j_long <- "'w_j' must have length equal to length(mu_mean) + 1 if length(mu_mean) > 1" error_w_j_short <- "'w_j' must have length 1 or 2 if length(mu_mean) = 1" error_w_j_sum <- "Sum over items in 'w_j' must equal 1 if length(w_j) > 1" checkmate::assert_numeric(mu_mean, any.missing = FALSE, .var.name = error_mu_mean) checkmate::assert_numeric(mu_sd, lower = 0, any.missing = FALSE, .var.name = error_mu_sd) checkmate::assertTRUE(all(mu_sd > 0), .var.name = error_mu_sd) checkmate::assertNumber(tau_scale, .var.name = error_tau_scale) checkmate::assertTRUE(tau_scale > 0, .var.name = error_tau_scale) checkmate::assert_numeric(w_j, lower = 0, upper = 1, any.missing = FALSE, .var.name = error_w_j) checkmate::assert_true(length(mu_mean) == length(mu_sd), .var.name = error_mu_mean_sd) if (length(mu_mean) > 1) { checkmate::assert_true(length(w_j) == length(mu_mean) + 1, .var.name = error_w_j_long) } else { checkmate::assert_true(length(w_j) %in% c(1, 2), .var.name = error_w_j_short) } if (length(w_j) > 1) { checkmate::assert_true(isTRUE(all.equal(sum(w_j), 1)), .var.name = error_w_j_sum) } prior_base <- list(mu_mean = mu_mean, mu_sd = mu_sd, tau_scale = tau_scale, w_j = w_j) if (is.null(w_nex) && is.null(mean_nex) && is.null(sd_nex)) { checkmate::assert_numeric(mu_j, any.missing = FALSE, .var.name = error_mu_j) checkmate::assert_numeric(tau_j, any.missing = FALSE, .var.name = error_tau_j) checkmate::assertTRUE(all(tau_j > 0), .var.name = error_tau_j) checkmate::assert_true(length(mu_j) == length(tau_j), .var.name = error_mu_j_tau_j) prior_extra <- list(mu_j = mu_j, tau_j = tau_j) } else { checkmate::assertNumeric(w_nex, any.missing = FALSE, lower = 0, upper = 1, .var.name = error_w_nex) checkmate::assertTRUE(isTRUE(all.equal(sum(w_nex), 1)), .var.name = error_w_nex) checkmate::assertTRUE(is.matrix(mean_nex), .var.name = error_mean_nex) checkmate::assertTRUE(is.matrix(sd_nex), .var.name = error_sd_nex) checkmate::assertTRUE(all(sd_nex > 0), .var.name = error_sd_nex) checkmate::assertTRUE(all(dim(mean_nex) == dim(sd_nex)), .var.name = error_dim) checkmate::assertTRUE(nrow(mean_nex) == length(w_nex), .var.name = error_dim) prior_extra <- list(w_nex = as.numeric(w_nex), mean_nex = mean_nex, sd_nex = sd_nex) } prior_parameters_list <- list(exnex = c(prior_base, prior_extra)) class(prior_parameters_list) <- "prior_parameters_list" return(prior_parameters_list) })(mu_mean = -1.38629436111989, mu_sd = 100, mu_j = c(-1.38629436111989, -1.38629436111989, -1.38629436111989), tau_j = c(100, 100, 100), tau_scale = 1, w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─basksim::adjust_lambda(...) at test-adjust_lambda.R:63:3 2. └─basksim:::adjust_lambda.exnex(...) 3. └─base::do.call(...) ── Error ('test-get_details.R:113:3'): get_details works for exnex ───────────── Error in `bhmbasket::setPriorParametersExNex(mu_mean = bhmbasket:::logit(0.15), mu_sd = 100, tau_scale = 0.75, mu_j = rep(bhmbasket:::logit(0.15), 3), tau_j = rep(100, 3), w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─base::suppressMessages(...) at test-get_details.R:113:3 2. │ └─base::withCallingHandlers(...) 3. └─bhmbasket::performAnalyses(...) [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 2.1.0
Check: tests
Result: ERROR Running ‘testthat.R’ [5m/13m] 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(basksim) > > test_check("basksim") Saving _problems/test-adjust_lambda-64.R Saving _problems/test-get_details-126.R [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] ══ Skipped tests (13) ══════════════════════════════════════════════════════════ • On CRAN (13): 'test-adjust_lambda.R:15:3', 'test-adjust_lambda.R:119:3', 'test-get_details.R:11:3', 'test-get_details.R:35:3', 'test-get_details.R:203:3', 'test-get_details.R:234:5', 'test-get_details.R:297:3', 'test-get_details.R:335:3', 'test-get_details.R:383:3', 'test-get_details.R:420:3', 'test-get_details.R:460:3', 'test-get_details.R:486:3', 'test-opt_design.R:19:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-adjust_lambda.R:63:3'): adjust_lambda works for exnex ────────── Error in `(function (mu_mean, mu_sd, tau_scale, mu_j = NULL, tau_j = NULL, w_j, w_nex = NULL, mean_nex = NULL, sd_nex = NULL) { error_mu_mean <- "Providing a numeric for the argument 'mu_mean'" error_mu_sd <- "Providing a positive numeric for the argument 'mu_sd'" error_tau_scale <- "Providing a positive numeric for the argument 'tau_scale'" error_mu_j <- "Providing a (vector of) numeric(s) for the argument 'mu_j'" error_tau_j <- "Providing a (vector of) positive numeric(s) for the argument 'tau_j'" error_w_j <- "Providing a numeric in (0, 1) for the argument 'w_j'" error_w_nex <- "Providing a numeric vector of weights in [0, 1] summing to 1 for the argument 'w_nex'" error_mean_nex <- "Providing a numeric matrix for the argument 'mean_nex'" error_sd_nex <- "Providing a positive numeric matrix for the argument 'sd_nex'" error_dim <- "'mean_nex' and 'sd_nex' must have the same dimensions, and nrow(mean_nex) must equal length(w_nex)" error_mu_mean_sd <- "'mu_mean' and 'mu_sd' must have same length" error_mu_j_tau_j <- "'mu_j' and 'tau_j' must have the same length" error_w_j_long <- "'w_j' must have length equal to length(mu_mean) + 1 if length(mu_mean) > 1" error_w_j_short <- "'w_j' must have length 1 or 2 if length(mu_mean) = 1" error_w_j_sum <- "Sum over items in 'w_j' must equal 1 if length(w_j) > 1" checkmate::assert_numeric(mu_mean, any.missing = FALSE, .var.name = error_mu_mean) checkmate::assert_numeric(mu_sd, lower = 0, any.missing = FALSE, .var.name = error_mu_sd) checkmate::assertTRUE(all(mu_sd > 0), .var.name = error_mu_sd) checkmate::assertNumber(tau_scale, .var.name = error_tau_scale) checkmate::assertTRUE(tau_scale > 0, .var.name = error_tau_scale) checkmate::assert_numeric(w_j, lower = 0, upper = 1, any.missing = FALSE, .var.name = error_w_j) checkmate::assert_true(length(mu_mean) == length(mu_sd), .var.name = error_mu_mean_sd) if (length(mu_mean) > 1) { checkmate::assert_true(length(w_j) == length(mu_mean) + 1, .var.name = error_w_j_long) } else { checkmate::assert_true(length(w_j) %in% c(1, 2), .var.name = error_w_j_short) } if (length(w_j) > 1) { checkmate::assert_true(isTRUE(all.equal(sum(w_j), 1)), .var.name = error_w_j_sum) } prior_base <- list(mu_mean = mu_mean, mu_sd = mu_sd, tau_scale = tau_scale, w_j = w_j) if (is.null(w_nex) && is.null(mean_nex) && is.null(sd_nex)) { checkmate::assert_numeric(mu_j, any.missing = FALSE, .var.name = error_mu_j) checkmate::assert_numeric(tau_j, any.missing = FALSE, .var.name = error_tau_j) checkmate::assertTRUE(all(tau_j > 0), .var.name = error_tau_j) checkmate::assert_true(length(mu_j) == length(tau_j), .var.name = error_mu_j_tau_j) prior_extra <- list(mu_j = mu_j, tau_j = tau_j) } else { checkmate::assertNumeric(w_nex, any.missing = FALSE, lower = 0, upper = 1, .var.name = error_w_nex) checkmate::assertTRUE(isTRUE(all.equal(sum(w_nex), 1)), .var.name = error_w_nex) checkmate::assertTRUE(is.matrix(mean_nex), .var.name = error_mean_nex) checkmate::assertTRUE(is.matrix(sd_nex), .var.name = error_sd_nex) checkmate::assertTRUE(all(sd_nex > 0), .var.name = error_sd_nex) checkmate::assertTRUE(all(dim(mean_nex) == dim(sd_nex)), .var.name = error_dim) checkmate::assertTRUE(nrow(mean_nex) == length(w_nex), .var.name = error_dim) prior_extra <- list(w_nex = as.numeric(w_nex), mean_nex = mean_nex, sd_nex = sd_nex) } prior_parameters_list <- list(exnex = c(prior_base, prior_extra)) class(prior_parameters_list) <- "prior_parameters_list" return(prior_parameters_list) })(mu_mean = -1.38629436111989, mu_sd = 100, mu_j = c(-1.38629436111989, -1.38629436111989, -1.38629436111989), tau_j = c(100, 100, 100), tau_scale = 1, w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─basksim::adjust_lambda(...) at test-adjust_lambda.R:63:3 2. └─basksim:::adjust_lambda.exnex(...) 3. └─base::do.call(...) ── Error ('test-get_details.R:113:3'): get_details works for exnex ───────────── Error in `bhmbasket::setPriorParametersExNex(mu_mean = bhmbasket:::logit(0.15), mu_sd = 100, tau_scale = 0.75, mu_j = rep(bhmbasket:::logit(0.15), 3), tau_j = rep(100, 3), w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─base::suppressMessages(...) at test-get_details.R:113:3 2. │ └─base::withCallingHandlers(...) 3. └─bhmbasket::performAnalyses(...) [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-clang

Version: 2.1.0
Check: tests
Result: ERROR Running ‘testthat.R’ [5m/17m] 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(basksim) > > test_check("basksim") Saving _problems/test-adjust_lambda-64.R Saving _problems/test-get_details-126.R [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] ══ Skipped tests (13) ══════════════════════════════════════════════════════════ • On CRAN (13): 'test-adjust_lambda.R:15:3', 'test-adjust_lambda.R:119:3', 'test-get_details.R:11:3', 'test-get_details.R:35:3', 'test-get_details.R:203:3', 'test-get_details.R:234:5', 'test-get_details.R:297:3', 'test-get_details.R:335:3', 'test-get_details.R:383:3', 'test-get_details.R:420:3', 'test-get_details.R:460:3', 'test-get_details.R:486:3', 'test-opt_design.R:19:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-adjust_lambda.R:63:3'): adjust_lambda works for exnex ────────── Error in `(function (mu_mean, mu_sd, tau_scale, mu_j = NULL, tau_j = NULL, w_j, w_nex = NULL, mean_nex = NULL, sd_nex = NULL) { error_mu_mean <- "Providing a numeric for the argument 'mu_mean'" error_mu_sd <- "Providing a positive numeric for the argument 'mu_sd'" error_tau_scale <- "Providing a positive numeric for the argument 'tau_scale'" error_mu_j <- "Providing a (vector of) numeric(s) for the argument 'mu_j'" error_tau_j <- "Providing a (vector of) positive numeric(s) for the argument 'tau_j'" error_w_j <- "Providing a numeric in (0, 1) for the argument 'w_j'" error_w_nex <- "Providing a numeric vector of weights in [0, 1] summing to 1 for the argument 'w_nex'" error_mean_nex <- "Providing a numeric matrix for the argument 'mean_nex'" error_sd_nex <- "Providing a positive numeric matrix for the argument 'sd_nex'" error_dim <- "'mean_nex' and 'sd_nex' must have the same dimensions, and nrow(mean_nex) must equal length(w_nex)" error_mu_mean_sd <- "'mu_mean' and 'mu_sd' must have same length" error_mu_j_tau_j <- "'mu_j' and 'tau_j' must have the same length" error_w_j_long <- "'w_j' must have length equal to length(mu_mean) + 1 if length(mu_mean) > 1" error_w_j_short <- "'w_j' must have length 1 or 2 if length(mu_mean) = 1" error_w_j_sum <- "Sum over items in 'w_j' must equal 1 if length(w_j) > 1" checkmate::assert_numeric(mu_mean, any.missing = FALSE, .var.name = error_mu_mean) checkmate::assert_numeric(mu_sd, lower = 0, any.missing = FALSE, .var.name = error_mu_sd) checkmate::assertTRUE(all(mu_sd > 0), .var.name = error_mu_sd) checkmate::assertNumber(tau_scale, .var.name = error_tau_scale) checkmate::assertTRUE(tau_scale > 0, .var.name = error_tau_scale) checkmate::assert_numeric(w_j, lower = 0, upper = 1, any.missing = FALSE, .var.name = error_w_j) checkmate::assert_true(length(mu_mean) == length(mu_sd), .var.name = error_mu_mean_sd) if (length(mu_mean) > 1) { checkmate::assert_true(length(w_j) == length(mu_mean) + 1, .var.name = error_w_j_long) } else { checkmate::assert_true(length(w_j) %in% c(1, 2), .var.name = error_w_j_short) } if (length(w_j) > 1) { checkmate::assert_true(isTRUE(all.equal(sum(w_j), 1)), .var.name = error_w_j_sum) } prior_base <- list(mu_mean = mu_mean, mu_sd = mu_sd, tau_scale = tau_scale, w_j = w_j) if (is.null(w_nex) && is.null(mean_nex) && is.null(sd_nex)) { checkmate::assert_numeric(mu_j, any.missing = FALSE, .var.name = error_mu_j) checkmate::assert_numeric(tau_j, any.missing = FALSE, .var.name = error_tau_j) checkmate::assertTRUE(all(tau_j > 0), .var.name = error_tau_j) checkmate::assert_true(length(mu_j) == length(tau_j), .var.name = error_mu_j_tau_j) prior_extra <- list(mu_j = mu_j, tau_j = tau_j) } else { checkmate::assertNumeric(w_nex, any.missing = FALSE, lower = 0, upper = 1, .var.name = error_w_nex) checkmate::assertTRUE(isTRUE(all.equal(sum(w_nex), 1)), .var.name = error_w_nex) checkmate::assertTRUE(is.matrix(mean_nex), .var.name = error_mean_nex) checkmate::assertTRUE(is.matrix(sd_nex), .var.name = error_sd_nex) checkmate::assertTRUE(all(sd_nex > 0), .var.name = error_sd_nex) checkmate::assertTRUE(all(dim(mean_nex) == dim(sd_nex)), .var.name = error_dim) checkmate::assertTRUE(nrow(mean_nex) == length(w_nex), .var.name = error_dim) prior_extra <- list(w_nex = as.numeric(w_nex), mean_nex = mean_nex, sd_nex = sd_nex) } prior_parameters_list <- list(exnex = c(prior_base, prior_extra)) class(prior_parameters_list) <- "prior_parameters_list" return(prior_parameters_list) })(mu_mean = -1.38629436111989, mu_sd = 100, mu_j = c(-1.38629436111989, -1.38629436111989, -1.38629436111989), tau_j = c(100, 100, 100), tau_scale = 1, w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─basksim::adjust_lambda(...) at test-adjust_lambda.R:63:3 2. └─basksim:::adjust_lambda.exnex(...) 3. └─base::do.call(...) ── Error ('test-get_details.R:113:3'): get_details works for exnex ───────────── Error in `bhmbasket::setPriorParametersExNex(mu_mean = bhmbasket:::logit(0.15), mu_sd = 100, tau_scale = 0.75, mu_j = rep(bhmbasket:::logit(0.15), 3), tau_j = rep(100, 3), w = 0.5)`: argument 6 matches multiple formal arguments Backtrace: ▆ 1. ├─base::suppressMessages(...) at test-get_details.R:113:3 2. │ └─base::withCallingHandlers(...) 3. └─bhmbasket::performAnalyses(...) [ FAIL 2 | WARN 0 | SKIP 13 | PASS 232 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc

Package blindrecalc

Current CRAN status: OK: 14

Package findn

Current CRAN status: OK: 14