CRAN Package Check Results for Package blapsr

Last updated on 2026-10-24 12:51:27 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.7.0 13.72 132.75 146.47 OK
r-devel-linux-x86_64-debian-gcc 0.7.0 9.29 72.59 81.88 ERROR
r-devel-linux-x86_64-fedora-clang 0.7.0 9.00 87.15 96.15 OK
r-devel-linux-x86_64-fedora-gcc 0.7.0 99.28 OK
r-devel-windows-x86_64 0.7.0 16.00 139.00 155.00 OK
r-patched-linux-x86_64 0.7.0 11.87 122.34 134.21 OK
r-release-linux-x86_64 0.7.0 13.57 123.60 137.17 OK
r-release-macos-arm64 0.7.0 3.00 34.00 37.00 OK
r-release-macos-x86_64 0.7.0 9.00 194.00 203.00 OK
r-release-windows-x86_64 0.7.0 17.00 131.00 148.00 OK
r-oldrel-macos-arm64 0.7.0 OK
r-oldrel-macos-x86_64 0.7.0 8.00 123.00 131.00 OK
r-oldrel-windows-x86_64 0.7.0 19.00 176.00 195.00 OK

Check Details

Version: 0.7.0
Check: examples
Result: ERROR Running examples in ‘blapsr-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: coxlps > ### Title: Fit a Cox proportional hazards regression model with > ### Laplace-P-splines. > ### Aliases: coxlps > > ### ** Examples > > > ### Example 1 (Simulated survival data) > > set.seed(3) > > # Simulate survival data with simsurvdata > betas <- c(0.13, 0.52, 0.30) > simul <- simsurvdata(a = 3.8, b = 2.2, n = 250, betas = betas , censperc = 20) > simul Sample size: 250 Censoring: Exponential Number of events: 199 Censoring percentage: 20.4% Weibull mean: 1.99 Weibull variance: 0.34 > simdat <- simul$survdata > plot(simul) # Plot survival data > > # Estimation with coxlps > fit <- coxlps(Surv(time, delta) ~ x1 + x2 + x3, data = simdat, K = 15) > # Compare coxlps and coxph > fit Formula: Surv(time, delta) ~ x1 + x2 + x3 Object class: "coxlps" Number of B-splines in basis: 15 Number of parametric coeffs.: 3 Latent vector dimension : 18 Penalty order : 2 Sample size : 250 Number of events: : 199 Effective dimension (ED) : 5.01 Estimated model coefficients: coef exp(coef) sd.post z x1 0.2167 1.2419 0.0697 3.1072 x2 0.4787 1.6140 0.0800 5.9818 x3 0.2023 1.2242 0.0831 2.4332 exp(coef) exp(-coef) lower.95 upper.95 x1 1.2419 0.8052 1.0830 1.4226 x2 1.6140 0.6196 1.3775 1.8863 x3 1.2242 0.8169 1.0384 1.4394 --- AIC.p = 468.5794 AIC.ED = 472.5963 BIC.p = 478.4593 BIC.ED = 489.0905 > summary(coxph(Surv(time, delta) ~ x1 + x2 + x3, data = simdat)) Call: coxph(formula = Surv(time, delta) ~ x1 + x2 + x3, data = simdat) n= 250, number of events= 199 coef exp(coef) se(coef) z Pr(>|z|) x1 0.20775 1.23091 0.06919 3.003 0.00268 ** x2 0.47557 1.60894 0.08002 5.943 2.8e-09 *** x3 0.18178 1.19936 0.08272 2.198 0.02798 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 exp(coef) exp(-coef) lower .95 upper .95 x1 1.231 0.8124 1.075 1.410 x2 1.609 0.6215 1.375 1.882 x3 1.199 0.8338 1.020 1.410 Concordance= 0.637 (se = 0.023 ) Likelihood ratio test= 45.5 on 3 df, p=7e-10 Wald test = 45.8 on 3 df, p=6e-10 Score (logrank) test = 45.95 on 3 df, p=6e-10 > > # Fitted baseline survival vs target > plot(fit, h0 = FALSE, cred.int = 0.95, overlay.km = TRUE) Error in a$specials[[i]] : subscript out of bounds Calls: plot ... survfit.coxph -> model.matrix.coxph -> delete.response -> off Execution halted Examples with CPU (user + system) or elapsed time > 5s user system elapsed amlps 3.75 0.055 5.281 Flavor: r-devel-linux-x86_64-debian-gcc