CRAN Package Check Results for Package horseshoe

Last updated on 2025-09-12 01:52:41 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.0 2.00 43.08 45.08 OK
r-devel-linux-x86_64-debian-gcc 0.2.0 1.73 32.34 34.07 ERROR
r-devel-linux-x86_64-fedora-clang 0.2.0 67.04 ERROR
r-devel-linux-x86_64-fedora-gcc 0.2.0 83.63 OK
r-devel-windows-x86_64 0.2.0 4.00 59.00 63.00 OK
r-patched-linux-x86_64 0.2.0 2.20 41.90 44.10 OK
r-release-linux-x86_64 0.2.0 2.03 42.21 44.24 OK
r-release-macos-arm64 0.2.0 36.00 OK
r-release-macos-x86_64 0.2.0 67.00 OK
r-release-windows-x86_64 0.2.0 4.00 61.00 65.00 OK
r-oldrel-macos-arm64 0.2.0 28.00 OK
r-oldrel-macos-x86_64 0.2.0 43.00 OK
r-oldrel-windows-x86_64 0.2.0 4.00 70.00 74.00 OK

Check Details

Version: 0.2.0
Check: examples
Result: ERROR Running examples in ‘horseshoe-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: HS.normal.means > ### Title: The horseshoe prior for the sparse normal means problem > ### Aliases: HS.normal.means > > ### ** Examples > > #Empirical Bayes example with 20 signals, rest is noise > #Posterior mean for the signals is plotted > #And variable selection is performed using the credible intervals > #And the credible intervals are plotted > truth <- c(rep(0, 80), rep(8, 20)) > data <- truth + rnorm(100, 1) > tau.hat <- HS.MMLE(data, Sigma2 = 1) > res.HS1 <- HS.normal.means(data, method.tau = "fixed", tau = tau.hat, + method.sigma = "fixed", Sigma2 = 1) [1] 1000 [1] 2000 [1] 3000 [1] 4000 [1] 5000 [1] 6000 > #Plot the posterior mean against the data (signals in blue) > plot(data, res.HS1$BetaHat, col = c(rep("black", 80), rep("blue", 20))) > #Find the selected betas (ideally, the last 20 are equal to 1) > HS.var.select(res.HS1, data, method = "intervals") [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 [75] 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > #Plot the credible intervals > library(Hmisc) Attaching package: ‘Hmisc’ The following objects are masked from ‘package:base’: format.pval, units > xYplot(Cbind(res.HS1$BetaHat, res.HS1$LeftCI, res.HS1$RightCI) ~ 1:100) Error in sRequire("lattice") : package lattice is required but not installed Calls: xYplot -> sRequire Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.2.0
Check: examples
Result: ERROR Running examples in ‘horseshoe-Ex.R’ failed The error most likely occurred in: > ### Name: HS.normal.means > ### Title: The horseshoe prior for the sparse normal means problem > ### Aliases: HS.normal.means > > ### ** Examples > > #Empirical Bayes example with 20 signals, rest is noise > #Posterior mean for the signals is plotted > #And variable selection is performed using the credible intervals > #And the credible intervals are plotted > truth <- c(rep(0, 80), rep(8, 20)) > data <- truth + rnorm(100, 1) > tau.hat <- HS.MMLE(data, Sigma2 = 1) > res.HS1 <- HS.normal.means(data, method.tau = "fixed", tau = tau.hat, + method.sigma = "fixed", Sigma2 = 1) [1] 1000 [1] 2000 [1] 3000 [1] 4000 [1] 5000 [1] 6000 > #Plot the posterior mean against the data (signals in blue) > plot(data, res.HS1$BetaHat, col = c(rep("black", 80), rep("blue", 20))) > #Find the selected betas (ideally, the last 20 are equal to 1) > HS.var.select(res.HS1, data, method = "intervals") [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 [75] 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > #Plot the credible intervals > library(Hmisc) Attaching package: ‘Hmisc’ The following objects are masked from ‘package:base’: format.pval, units > xYplot(Cbind(res.HS1$BetaHat, res.HS1$LeftCI, res.HS1$RightCI) ~ 1:100) Error in sRequire("lattice") : package lattice is required but not installed Calls: xYplot -> sRequire Execution halted Flavor: r-devel-linux-x86_64-fedora-clang