CRAN Package Check Results for Package HiddenMarkov

Last updated on 2024-03-28 17:49:30 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.8-13 7.31 73.91 81.22 OK
r-devel-linux-x86_64-debian-gcc 1.8-13 5.35 54.53 59.88 OK
r-devel-linux-x86_64-fedora-clang 1.8-13 98.49 OK
r-devel-linux-x86_64-fedora-gcc 1.8-13 97.28 OK
r-devel-windows-x86_64 1.8-13 9.00 245.00 254.00 ERROR
r-patched-linux-x86_64 1.8-13 9.14 72.25 81.39 OK
r-release-linux-x86_64 1.8-13 7.65 73.79 81.44 OK
r-release-macos-arm64 1.8-13 30.00 OK
r-release-macos-x86_64 1.8-13 52.00 OK
r-release-windows-x86_64 1.8-13 11.00 93.00 104.00 OK
r-oldrel-macos-arm64 1.8-13 30.00 OK
r-oldrel-windows-x86_64 1.8-13 19.00 103.00 122.00 OK

Check Details

Version: 1.8-13
Check: tests
Result: ERROR Running 'dthmm-mmglm1-gaussian.R' [2s] Comparing 'dthmm-mmglm1-gaussian.Rout' to 'dthmm-mmglm1-gaussian.Rout.save' ... OK Running 'mmglm0-mmglm1-binomial.R' [169s] Running 'mmglm0-mmglm1-gaussian.R' [3s] Comparing 'mmglm0-mmglm1-gaussian.Rout' to 'mmglm0-mmglm1-gaussian.Rout.save' ... OK Running 'mmglm0-mmglm1-gaussian1.R' [2s] Comparing 'mmglm0-mmglm1-gaussian1.Rout' to 'mmglm0-mmglm1-gaussian1.Rout.save' ... OK Running the tests in 'tests/mmglm0-mmglm1-binomial.R' failed. Complete output: > # Compare mmglm0 and mmglm1 > # Gaussian with identity link function > # R CMD BATCH --no-save mmglm0-mmglm1-binomial.R mmglm0-mmglm1-binomial.Rout.save > > library(HiddenMarkov) > > > delta <- c(0,1) > > Pi <- matrix(c(0.8, 0.2, + 0.3, 0.7), + byrow=TRUE, nrow=2) > > beta <- matrix(c(0.1, -0.1, + 1.0, 5.0), + byrow=TRUE, nrow=2) > > sd <- c(1, 2) > > n <- 5000 > > # Use different numbers of Bernoulli trials > set.seed(5) > x <- list(size=rpois(n, 10)+1) > > #-------------------------------------------------------- > # Gaussian with identity link function > # using mmglm0 > > x0 <- mmglm0(x, Pi, delta, family="binomial", link="logit", + beta=beta, sigma=sd, msg=FALSE) > > x0 <- simulate(x0, nsim=n, seed=10) > > x0 <- BaumWelch(x0, bwcontrol(prt=FALSE)) > > print(summary(x0)) $variable.names [1] "size" "x1" "y" $delta [1] 0 1 $Pi [,1] [,2] [1,] 0.7910361 0.2089639 [2,] 0.2930963 0.7069037 $nonstat [1] TRUE $beta [,1] [,2] [1,] 0.06952233 -0.07849712 [2,] 1.04381456 5.03532098 $sigma [1] 0.9854419 0.9982205 $family [1] "binomial" $glmformula y ~ x1 <environment: 0x0000023351631a00> $link [1] "logit" $n [1] 5000 > > #-------------------------------------------------------- > # Now embed this data into a mmglm1 object > > glmformula <- formula(y ~ x1) > glmfamily <- binomial(link="logit") > Xdesign <- model.matrix(glmformula, data=x0$x) > > x1 <- mmglm1(x0$x$y, Pi, delta, glmfamily, beta, Xdesign, sigma=sd, + size=x$size, msg=FALSE) > > x1 <- BaumWelch(x1, bwcontrol(prt=FALSE)) > > print(summary(x1)) $delta [1] 0 1 $Pi [,1] [,2] [1,] 0.7910361 0.2089639 [2,] 0.2930963 0.7069037 $nonstat [1] TRUE $beta State 1 State 2 (Intercept) 0.06952233 -0.07849712 x1 1.04381456 5.03532098 $sigma [1] 0.9854419 0.9982205 $glmfamily Family: binomial Link function: logit $n [1] 5000 > > #-------------------------------------------------------- > # Compare Models > > if (abs(logLik(x0)-logLik(x1)) > 1e-06) + warning("WARNING: See tests/mmglm0-mmglm1.R-binomial, log-likelihoods are different") > > if (any(Viterbi(x0)!=Viterbi(x1))) + warning("WARNING: See tests/mmglm0-mmglm1-binomial.R, Viterbi paths are different") > > if (any(abs(residuals(x0)-residuals(x1)) > 1e-06)) + warning("WARNING: See tests/mmglm0-mmglm1-binomial.R, residuals are different") > > > > proc.time() user system elapsed 3.48 0.31 3.78 Flavor: r-devel-windows-x86_64