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BayesianMCPMod CRAN Comments

Maintainer

'Stephan Wojciekowski stephan.wojciekowski@boehringer-ingelheim.com'

Test environments

  • Local aarch64-apple-darwin20, R 4.4.2

  • Winbuilder x86_64-w64-mingw32, Windows Server, R under development (unstable) (2025-02-05 r87692 ucrt)

  • Macbuilder aarch64-apple-darwin20, macOS Ventura 13.3.1, R version 4.4.2 (2024-10-31)

  • Github Linux / ubuntu-latest (release)

  • Github Mac / macos-latest (release)

  • Github windows, all R versions on GitHub Actions windows-latest

R CMD check results

Local aarch64-apple-darwin20, Windows Server, R 4.4.2

0 errors √ | 0 warnings √ | 0 notes √

Winbuilder x86_64-w64-mingw32, macOS Ventura 13.3.1, R under development (unstable) (2025-02-05 r87692 ucrt)

  • DONE Status: OK

Macbuilder aarch64-apple-darwin20, macOS Ventura 13.3.1, R version 4.4.2 (2024-10-31)

  • DONE Status: OK

Github Linux / ubuntu-latest (release)

  • DONE Status: OK

Github Mac / macos-latest (release)

  • DONE Status: OK

Windows / windows-latest (release)

  • checking for detritus in the temp directory ... NOTE Found the following files/directories: 'Rscript420e8038' 'Rscripta4ce8028'
  • DONE Status: 1 NOTE

-> This note seems is related with the parallelization on the github server and does not occur on the Winbuilder server.

From NEWS.md

BayesianMCPMod 1.0.2 (06-Feb-2025)

  • Addition of new vignette comparing frequentist and Bayesian MCPMod using vague priors
  • Extension of getPosterior to allow the input of a fully populated variance-covariance matrix
  • Added the non-monotonic model shapes beta and quadratic
  • New argument in assessDesign() to skip the Mod part of Bayesian MCPMod
  • Additional tests

BayesianMCPMod 1.0.1 (03-Apr-2024)

  • Re-submission of the 'BayesianMCPMod' package
  • Removed a test that occasionally failed on the fedora CRAN test system
  • Fixed a bug that would return wrong bootstrapped quantiles in getBootstrappedQuantiles()
  • Added getBootstrapSamples(), a separate function for bootstrapping samples

BayesianMCPMod 1.0.0 (31-Dec-2023)

  • Initial release of the 'BayesianMCPMod' package
  • Special thanks to Jana Gierse, Bjoern Bornkamp, Chen Yao, Marius Thoma & Mitchell Thomann for their review and valuable comments
  • Thanks to Kevin Kunzmann for R infrastructure support and to Frank Fleischer for methodological support