CRAN Package Check Results for Package confintROB

Last updated on 2025-12-12 09:48:48 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0-2 10.49 117.04 127.53 OK
r-devel-linux-x86_64-debian-gcc 1.0-2 7.82 65.21 73.03 ERROR
r-devel-linux-x86_64-fedora-clang 1.0-2 60.00 148.48 208.48 OK
r-devel-linux-x86_64-fedora-gcc 1.0-2 20.00 163.54 183.54 OK
r-devel-windows-x86_64 1.0-2 11.00 116.00 127.00 OK
r-patched-linux-x86_64 1.0-2 10.84 109.95 120.79 OK
r-release-linux-x86_64 1.0-2 10.07 109.95 120.02 OK
r-release-macos-arm64 1.0-2 OK
r-release-macos-x86_64 1.0-2 8.00 97.00 105.00 OK
r-release-windows-x86_64 1.0-2 12.00 115.00 127.00 OK
r-oldrel-macos-arm64 1.0-2 OK
r-oldrel-macos-x86_64 1.0-2 8.00 98.00 106.00 OK
r-oldrel-windows-x86_64 1.0-2 15.00 155.00 170.00 OK

Check Details

Version: 1.0-2
Check: tests
Result: ERROR Running ‘confintrob_test.R’ [3s/3s] Running ‘parallelTest.R’ [2s/6s] Running ‘varComprob_createParamSampleFunction.R’ [2s/3s] Running the tests in ‘tests/confintrob_test.R’ failed. Complete output: > require(confintROB) Loading required package: confintROB > require(lme4) Loading required package: lme4 Loading required package: Matrix > require(robustlmm) Loading required package: robustlmm Warning message: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called 'robustlmm' > > test <- function(object, ...) { + doTest <- function(method, ...) { + cat( + "Running test for object of class ", + class(object), + " with arguments method = ", + method, + "\n" + ) + set.seed(1234) + result <- + confintROB( + object = object, + level = .95, + method = method, + nsim = 10, + boot.type = "parametric", + clusterID = "Subject", + ... + ) + print(result, digits = 2) + } + + for (method in c("boot", "BCa", "Wald")) { + doTest(method, ...) + } + } > > test.wild <- function(object, ...) { + cat("Running test.wild for object of class ", class(object), "\n") + set.seed(123) + y <- getME(object, "y") + X <- as.matrix(getME(object, "X")) + id <- getME(object, "flist")[[1]] + bet <- unname(fixef(object)) + result <- + confintROB:::createWildSampleFunction(y = y, + X = X, + id = id, + bet = bet)(1) + print(result, digits = 5) + } > > > control <- lmerControl(check.conv.grad = "ignore") > > model.ds.ML <- + lmer(Yield ~ (1 | Batch), + Dyestuff, + REML = FALSE, + control = control) > print(summary(model.ds.ML), digits = 2) Linear mixed model fit by maximum likelihood ['lmerMod'] Formula: Yield ~ (1 | Batch) Data: Dyestuff Control: control AIC BIC logLik -2*log(L) df.resid 333.3 337.5 -163.7 327.3 27 Scaled residuals: Min 1Q Median 3Q Max -1.43 -0.80 0.15 0.77 1.80 Random effects: Groups Name Variance Std.Dev. Batch (Intercept) 1388 37 Residual 2451 50 Number of obs: 30, groups: Batch, 6 Fixed effects: Estimate Std. Error t value (Intercept) 1528 18 86 > test(model.ds.ML) Running test for object of class lmerMod with arguments method = boot Ignoring argument 'clusterID' as it's not needed for this combination of arguments 2.5 % 97.5 % (Intercept) 1503 1535 Sigma Batch (Intercept) 17 42 Sigma Residual 40 61 attr(,"fullResults") Full results of confintROB, a list with components: "Percentile", "bootstrap_estimates" Running test for object of class lmerMod with arguments method = BCa Ignoring argument 'clusterID' as it's not needed for this combination of arguments 2.5 % 97.5 % (Intercept) 1500 1534 Sigma Batch (Intercept) 32 44 Sigma Residual 41 62 attr(,"fullResults") Full results of confintROB, a list with components: "BCa", "Percentile", "bootstrap_estimates", "biasBCa", "acc" Running test for object of class lmerMod with arguments method = Wald 2.5 % 97.5 % (Intercept) 1493 1562 > test.wild(model.ds.ML, .export = "control") Running test.wild for object of class lmerMod [[1]] 1 2 3 4 5 6 7 8 9 10 11 1516.5 1582.6 1582.6 1532.2 1494.4 1548.1 1572.9 1465.6 1581.1 1473.9 1485.0 12 13 14 15 16 17 18 19 20 21 22 1513.3 1478.7 1538.5 1507.0 1391.4 1383.1 1638.9 1424.4 1556.4 1638.9 1696.6 23 24 25 26 27 28 29 30 1506.9 1704.9 1688.4 1532.2 1573.2 1576.3 1557.4 1579.5 > > model.ds.DAStau <- + rlmer( + Yield ~ (1 | Batch), + Dyestuff, + rho.sigma.e = psi2propII(smoothPsi, k = 2.28), + rho.b = chgDefaults(smoothPsi, k = 5.14, s = 10), + rho.sigma.b = chgDefaults(smoothPsi, k = 5.14, s = 10), + init = function(...) + lmer(..., control = control) + ) Error in rlmer(Yield ~ (1 | Batch), Dyestuff, rho.sigma.e = psi2propII(smoothPsi, : could not find function "rlmer" Execution halted Running the tests in ‘tests/varComprob_createParamSampleFunction.R’ failed. Complete output: > require(confintROB) Loading required package: confintROB > require(lme4) Loading required package: lme4 Loading required package: Matrix > require(robustvarComp) Loading required package: robustvarComp Warning message: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called 'robustvarComp' > > test.varComprob <- + function(object, data = sleepstudy) { + cat("Running test for object of class ", class(object), "\n") + sample <- confintROB:::createParamSampleFunction(model = object, + data = data) + set.seed(123) + result11 <- c(sample(1), sample(1)) + set.seed(123) + result2 <- sample(2) + names(result11) <- names(result2) + stopifnot(all.equal(result11, result2)) + return(result2) + } > > participant <- sleepstudy$Subject > within <- sleepstudy$Days > > # Build the argument "groups" of the varComprob() function > n <- length(unique(participant)) # the number of participants > J <- + length(unique(within)) # the number of repeated observations per participant > groups <- + cbind(rep(1:J, each = n), rep((1:n), J)) # a numeric matrix with two columns used to group the observations according to participant. > > # Build the argument "varcov" of the varComprob() function > z1 <- + rep(1, J) #Value for intercept (=1) for the J observations by clusters > z2 <- unique(within) # Value for the time variable > > K <- + list( + # Matrix for intercept + sigma2_u0 = tcrossprod(z1, z1), + # Matrix of interaction Intercept by time variable + Covariance = tcrossprod(z1, z2) + tcrossprod(z2, z1), + # Matrix for time variable + sigma2_u1 = tcrossprod(z2, z2) + ) > > # Estimation with S-estimator > suppressWarnings( + model.S <- + varComprob( + Reaction ~ 1 + Days, + groups = groups, + data = sleepstudy, + varcov = K, + control = varComprob.control( + lower = c(0, -Inf, 0), + method = "S", + psi = "rocke", + max.it = 1, + init = list( + beta = c("(Intercept)" = 253.835569743834, Days = 10.7736608268214), + gamma = c( + sigma2_u0 = 1.59549700005736, + Covariance = -0.0711447985744645, + sigma2_u1 = 0.0765023178239254 + ), + eta0 = c("error variance" = 692.556625895202), + scale = 10752.1432565101 + ) + ) + ) + ) Error in varComprob(Reaction ~ 1 + Days, groups = groups, data = sleepstudy, : could not find function "varComprob" Execution halted Flavor: r-devel-linux-x86_64-debian-gcc