CRAN Package Check Results for Package VEwaningVariant

Last updated on 2026-10-24 03:56:25 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.4 108.04 100.83 208.87 OK
r-devel-linux-x86_64-debian-gcc 1.4 69.67 73.97 143.64 ERROR
r-devel-linux-x86_64-fedora-clang 1.4 78.00 67.52 145.52 OK
r-devel-linux-x86_64-fedora-gcc 1.4 76.00 65.68 141.68 OK
r-devel-windows-x86_64 1.4 127.00 184.00 311.00 OK
r-patched-linux-x86_64 1.4 92.80 94.49 187.29 OK
r-release-linux-x86_64 1.4 90.10 89.72 179.82 OK
r-release-macos-arm64 1.4 20.00 12.00 32.00 OK
r-release-macos-x86_64 1.4 59.00 72.00 131.00 OK
r-release-windows-x86_64 1.4 123.00 113.00 236.00 OK
r-oldrel-macos-arm64 1.4 OK
r-oldrel-macos-x86_64 1.4 52.00 55.00 107.00 OK
r-oldrel-windows-x86_64 1.4 138.00 147.00 285.00 OK

Check Details

Version: 1.4
Check: examples
Result: ERROR Running examples in ‘VEwaningVariant-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: veWaningVariant > ### Title: Estimation of Vaccine Efficacy Over Time - Variant Aware > ### Aliases: veWaningVariant > > ### ** Examples > > ## Don't show: > RcppArmadillo::armadillo_throttle_cores(2) > ## End(Don't show) > data(variantData) > > set.seed(1234) > > ind <- sample(1:nrow(variantData), 2000) > # NOTE: This sample size is chosen for example only -- larger data sets > # should be used. > > # no weighting -- variant 1 infection only > > res_noWgt <- veWaningVariant(data = variantData[ind,], + L = 52.0, + variant = 1L, + gFunc = 'piece', + v = c(5.0,10.0)) no models provided for weights -- weights = 1 verifying inputs 226 placebo participants refused vaccine after unblinding 676 placebo participants accepted vaccine after unblinding 1687 participants were censored 31 participants experienced variant 1 infection 42 participants experienced variant 2 infection 14 participants experienced variant 3 infection only variant infections 1 included in analysis < 10% (1/31) of infections occurred during the unblinded phase; only the blinded phase is included in analysis estimating theta iteration: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 > > # censoring only weighting -- variant 1 infection only > > res_cens <- veWaningVariant(data = variantData[ind,], + L = 52.0, + variant = 1L, + modelCensor0 = ~ X1+X2, + modelCensor1 = ~ X1+X2, + gFunc = 'piece', + v = c(5.0,10.0)) weighting depends only on censoring dynamic verifying inputs 226 placebo participants refused vaccine after unblinding 676 placebo participants accepted vaccine after unblinding 1687 participants were censored 31 participants experienced variant 1 infection 42 participants experienced variant 2 infection 14 participants experienced variant 3 infection only variant infections 1 included in analysis < 10% (1/31) of infections occurred during the unblinded phase; only the blinded phase is included in analysis performing regressions censoring Error in a$specials[[i]] : subscript out of bounds Calls: veWaningVariant -> .fitCensor -> .censorFit Execution halted Flavor: r-devel-linux-x86_64-debian-gcc