CRAN Package Check Results for Package snSMART

Last updated on 2026-03-19 22:53:27 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.4 7.50 69.82 77.32 OK
r-devel-linux-x86_64-debian-gcc 0.2.4 5.25 43.02 48.27 ERROR
r-devel-linux-x86_64-fedora-clang 0.2.4 12.00 104.01 116.01 OK
r-devel-linux-x86_64-fedora-gcc 0.2.4 13.00 105.74 118.74 OK
r-devel-macos-arm64 0.2.4 2.00 18.00 20.00 OK
r-devel-windows-x86_64 0.2.4 9.00 93.00 102.00 OK
r-patched-linux-x86_64 0.2.4 7.62 60.16 67.78 OK
r-release-linux-x86_64 0.2.4 6.35 59.44 65.79 OK
r-release-macos-arm64 0.2.4 OK
r-release-macos-x86_64 0.2.4 5.00 62.00 67.00 OK
r-release-windows-x86_64 0.2.4 8.00 91.00 99.00 OK
r-oldrel-macos-arm64 0.2.4 OK
r-oldrel-macos-x86_64 0.2.4 5.00 52.00 57.00 OK
r-oldrel-windows-x86_64 0.2.4 12.00 105.00 117.00 OK

Check Details

Version: 0.2.4
Check: examples
Result: ERROR Running examples in ‘snSMART-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: group_seq > ### Title: BJSM method for interim analysis and final analysis of group > ### sequential trial design > ### Aliases: group_seq print.summary.group_seq print.group_seq > > ### ** Examples > > mydata <- groupseqDATA_look1 > > result1 <- group_seq( + data = mydata, interim = TRUE, drop_threshold_pair = c(0.5, 0.4), + prior_dist = c("beta", "beta", "pareto"), pi_prior = c(0.4, 1.6, 0.4, 1.6, 0.4, 1.6), + beta_prior = c(1.6, 0.4, 3, 1), MCMC_SAMPLE = 6000, n.adapt = 1000, n_MCMC_chain = 1 + ) Interim Analysis Outcome: Threshold tau_l is set to: 0.5 Threshold psi_l is set to: 0.4 Step 1: Arm C's interim posterior probability of having the greatest response is bigger than threshold 0.5 Step 2: Arm A's interim posterior probability of having the lowest response is higher Arm A is dropped > > summary(result1) Arm A is dropped Iterations = 1101:7100 Thinning interval = 1 Number of chains = 1 Sample size per chain = 6000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE beta[1] 0.777 0.2150 0.00278 0.00644 beta[2] 1.246 0.2883 0.00372 0.01093 beta[3] 0.695 0.2787 0.00360 0.00781 beta[4] 1.350 0.3187 0.00411 0.00897 beta[5] 0.838 0.1957 0.00253 0.00697 beta[6] 1.208 0.2051 0.00265 0.00651 pi[1] 0.290 0.0899 0.00116 0.00182 pi[2] 0.423 0.0838 0.00108 0.00178 pi[3] 0.572 0.1093 0.00141 0.00256 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% beta[1] 0.281 0.634 0.839 0.966 1.000 beta[2] 1.005 1.064 1.153 1.320 2.051 beta[3] 0.101 0.479 0.770 0.953 1.000 beta[4] 1.011 1.115 1.262 1.504 2.182 beta[5] 0.307 0.753 0.920 0.987 1.000 beta[6] 1.005 1.063 1.151 1.287 1.736 pi[1] 0.135 0.226 0.284 0.347 0.479 pi[2] 0.263 0.366 0.422 0.479 0.590 pi[3] 0.353 0.497 0.574 0.648 0.779 > > > mydata <- groupseqDATA_full > result2 <- group_seq( + data = mydata, interim = FALSE, prior_dist = c("beta", "beta", "pareto"), + pi_prior = c(0.4, 1.6, 0.4, 1.6, 0.4, 1.6), + beta_prior = c(1.6, 0.4, 3, 1), MCMC_SAMPLE = 6000, n.adapt = 1000, + n_MCMC_chain = 1, ci = 0.95, DTR = TRUE + ) Error in update.jags(model, n.iter, ...) : Error in node beta[5] Slicer stuck at value with infinite density Calls: group_seq ... do.call -> <Anonymous> -> jags.samples -> update.jags Execution halted Flavor: r-devel-linux-x86_64-debian-gcc