CRAN Package Check Results for Package TESS

Last updated on 2015-02-05 23:50:40.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2.1 0.97 15.58 16.55 NOTE
r-devel-linux-x86_64-debian-gcc 1.2.1 0.84 15.12 15.96 NOTE
r-devel-linux-x86_64-fedora-clang 1.2.1 31.88 NOTE
r-devel-linux-x86_64-fedora-gcc 1.2.1 31.77 NOTE
r-devel-osx-x86_64-clang 1.2.1 39.41 OK
r-devel-windows-ix86+x86_64 1.2.1 5.00 25.00 30.00 OK
r-patched-linux-x86_64 1.2.1 1.02 18.41 19.43 NOTE
r-patched-solaris-sparc 1.2.1 227.30 OK
r-patched-solaris-x86 1.2.1 53.80 OK
r-release-linux-ix86 1.2.1 1.31 24.96 26.27 NOTE
r-release-linux-x86_64 1.2.1 0.98 18.61 19.59 NOTE
r-release-osx-x86_64-mavericks 1.2.1 OK
r-release-osx-x86_64-snowleopard 1.2.1 OK
r-release-windows-ix86+x86_64 1.2.1 7.00 30.00 37.00 OK
r-oldrel-windows-ix86+x86_64 1.2.1 5.00 32.00 37.00 OK

Check Details

Version: 1.2.1
Check: Rd line widths
Result: NOTE
    Rd file 'tess.PosteriorPrediction.Rd':
     \examples lines wider than 100 characters:
     # We first run an MCMC to obtain samples from the posterior distribution and then simulate the posterior predictive distribution.
     # Note, the number of iterations and the burnin is too small here and should be adapted for real analyses
    
    Rd file 'tess.PosteriorPredictiveTest.Rd':
     \examples lines wider than 100 characters:
     # We first run an MCMC to obtain samples from the posterior distribution and then simulate the posterior predictive distribution.
     # Note, the number of iterations and the burnin is too small here and should be adapted for real analyses
    
    Rd file 'tess.mcmc.Rd':
     \examples lines wider than 100 characters:
     # Note, the number of iterations and the burnin is too small here and should be adapted for real analyses
     samples <- tess.mcmc(likelihood,priors,runif(2,0,1),logTransforms=c(TRUE,TRUE),delta=c(0.1,0.1),iterations=100,burnin=20)
    
    Rd file 'tess.steppingStoneSampling.Rd':
     \examples lines wider than 100 characters:
     # Note, the number of iterations, the burnin and the number of stepping stones is too small here and should be adapted for real analyse ... [TRUNCATED]
     marginalLikelihood <- tess.steppingStoneSampling(likelihood,priors,runif(2,0,1),c(TRUE,TRUE),10,10,K=4)
    
    These lines will be truncated in the PDF manual.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-ix86, r-release-linux-x86_64