CRAN Package Check Results for Package survey

Last updated on 2026-07-22 23:58:22 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 4.5 56.75 421.45 478.20 OK
r-devel-linux-x86_64-debian-gcc 4.5 36.15 308.30 344.45 ERROR
r-devel-linux-x86_64-fedora-clang 4.5 92.00 697.34 789.34 OK
r-devel-linux-x86_64-fedora-gcc 4.5 39.00 281.56 320.56 OK
r-devel-windows-x86_64 4.5 62.00 451.00 513.00 OK
r-patched-linux-x86_64 4.5 50.87 399.04 449.91 OK
r-release-linux-x86_64 4.5 53.02 399.93 452.95 OK
r-release-macos-arm64 4.5 11.00 100.00 111.00 OK
r-release-macos-x86_64 4.5 33.00 424.00 457.00 OK
r-release-windows-x86_64 4.5 63.00 462.00 525.00 OK
r-oldrel-macos-arm64 4.5 OK
r-oldrel-macos-x86_64 4.5 38.00 682.00 720.00 OK
r-oldrel-windows-x86_64 4.5 74.00 590.00 664.00 OK

Check Details

Version: 4.5
Check: tests
Result: ERROR Running ‘3stage2phase.R’ [2s/3s] Running ‘DBIcheck.R’ [3s/3s] Running ‘anova-svycoxph.R’ [2s/3s] Running ‘api.R’ [2s/2s] Running ‘badcal.R’ [2s/2s] Comparing ‘badcal.Rout’ to ‘badcal.Rout.save’ ... OK Running ‘brewer_cpp.R’ [2s/2s] Running ‘by_covmat_nodrop.R’ [3s/4s] Running ‘bycovmat.R’ [2s/3s] Running ‘caleg.R’ [3s/4s] Running ‘check.R’ [2s/2s] Comparing ‘check.Rout’ to ‘check.Rout.save’ ... OK Running ‘confintrep.R’ [2s/3s] Running ‘contrast-replicates.R’ [2s/2s] Running ‘coxph-termtest.R’ [2s/3s] Running ‘deff.R’ [2s/2s] Comparing ‘deff.Rout’ to ‘deff.Rout.save’ ... OK Running ‘defftest.R’ [2s/2s] Running ‘degf-subset.R’ [2s/2s] Running ‘degf-svrepdesign.R’ [2s/2s] Running ‘domain.R’ [2s/2s] Comparing ‘domain.Rout’ to ‘domain.Rout.save’ ... OK Running ‘fpc.R’ [2s/2s] Running ‘glm-scoping.R’ [2s/2s] Running ‘inf_cal_test.R’ [3s/4s] Running ‘kalton.R’ [2s/2s] Comparing ‘kalton.Rout’ to ‘kalton.Rout.save’ ... OK Running ‘logranktest.R’ [2s/2s] Running ‘lonely.psu.R’ [2s/3s] Comparing ‘lonely.psu.Rout’ to ‘lonely.psu.Rout.save’ ... OK Running ‘mf_frames2.R’ [2s/2s] Running ‘mf_subpop.R’ [2s/2s] Running ‘mtcars-var.R’ [2s/2s] Running ‘multiphase_simple.R’ [3s/4s] Running ‘multistage-rcpp.R’ [2s/2s] Running ‘multistage.R’ [2s/2s] Running ‘na_action.R’ [2s/2s] Running ‘na_weights.R’ [2s/2s] Running ‘newquantile.R’ [2s/3s] Running ‘nwts-cch.R’ [3s/4s] Running ‘nwts.R’ [3s/4s] Comparing ‘nwts.Rout’ to ‘nwts.Rout.save’ ... OK Running ‘poisson.R’ [2s/2s] Running ‘pps.R’ [2s/2s] Running ‘predict-NA.R’ [2s/2s] Running ‘qrule-swiss.R’ [2s/2s] Running ‘quantile.R’ [3s/3s] Comparing ‘quantile.Rout’ to ‘quantile.Rout.save’ ... OK Running ‘quantiles-chile.R’ [2s/3s] Running ‘rakecheck.R’ [2s/3s] Running ‘raowuboot.R’ [2s/2s] Comparing ‘raowuboot.Rout’ to ‘raowuboot.Rout.save’ ... OK Running ‘regTermTest-missing.R’ [2s/2s] Running ‘regpredict.R’ [2s/2s] Comparing ‘regpredict.Rout’ to ‘regpredict.Rout.save’ ... OK Running ‘rss_scores.R’ [2s/3s] Running ‘scoping.R’ [2s/2s] Running ‘survcurve.R’ [5s/7s] Comparing ‘survcurve.Rout’ to ‘survcurve.Rout.save’ ... OK Running ‘svyby-strings.R’ [2s/2s] Running ‘svyby_bug.R’ [2s/2s] Running ‘svyby_se.R’ [2s/2s] Running ‘svycontrast.R’ [2s/2s] Running ‘svyivreg-var.R’ [2s/2s] Running ‘svyivreg.R’ [2s/2s] Running ‘svyolr-rake-subset.R’ [2s/2s] Running ‘svyolr.R’ [2s/2s] Running ‘testthat.R’ [4s/5s] Running ‘toy_example_for_postStratify.R’ [2s/2s] Running ‘twophase.R’ [3s/4s] Comparing ‘twophase.Rout’ to ‘twophase.Rout.save’ ... OK Running the tests in ‘tests/rakecheck.R’ failed. Complete output: > library(survey) Loading required package: grid Loading required package: Matrix Loading required package: survival Attaching package: 'survey' The following object is masked from 'package:graphics': dotchart > > data(api) > dclus1 <- svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) > rclus1 <- as.svrepdesign(dclus1) > > ## population marginal totals for each stratum > pop.types <- data.frame(stype=c("E","H","M"), Freq=c(4421,755,1018)) > pop.schwide <- data.frame(sch.wide=c("No","Yes"), Freq=c(1072,5122)) > > rclus1r <- rake(rclus1, list(~stype,~sch.wide), list(pop.types, pop.schwide), + control=list(epsilon=1e-10,maxit=30)) > > svymean(~api00, rclus1r) mean SE api00 641.23 26.874 > svytotal(~enroll, rclus1r) total SE enroll 3647280 463582 > > ff<-~stype+sch.wide > poptotals<-colSums(model.matrix(ff,model.frame(ff,apipop))) > rclus1g<-calibrate(rclus1, ~stype+sch.wide, poptotals,calfun="raking",tol=1e-10) > > svymean(~api00,rclus1g) mean SE api00 641.23 26.874 > svytotal(~enroll,rclus1g) total SE enroll 3647280 463582 > > all.equal(as.vector(weights(rclus1g)/weights(rclus1r)),rep(1,183)) [1] "Numeric: lengths (2745, 183) differ" > > ## Do it for a design without replicate weights > dclus1r<-rake(dclus1, list(~stype,~sch.wide), list(pop.types, pop.schwide), + control=list(epsilon=1e-10,maxit=30)) > > svymean(~api00, dclus1r) mean SE api00 641.23 23.704 > svytotal(~enroll, dclus1r) total SE enroll 3647280 400603 > > dclus1g<-calibrate(dclus1, ~stype+sch.wide, poptotals,calfun="raking",tol=1e-10) > > svymean(~api00,dclus1g) mean SE api00 641.23 23.704 > svytotal(~enroll,dclus1g) total SE enroll 3647280 400603 > > all.equal(as.vector(weights(dclus1g)/weights(dclus1r)),rep(1,183)) [1] TRUE > > > ## Example of raking with partial joint distributions > pop.table <- xtabs(~stype+sch.wide,apipop) > pop.imp<-data.frame(comp.imp=c("No","Yes"),Freq=c(1712,4482)) > dclus1r2<-rake(dclus1, list(~stype+sch.wide, ~comp.imp), + list(pop.table, pop.imp), + control=list(epsilon=1e-10,maxit=30)) Warning message: In rake(dclus1, list(~stype + sch.wide, ~comp.imp), list(pop.table, :*** buffer overflow detected ***: terminated Aborted Flavor: r-devel-linux-x86_64-debian-gcc