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Provides analytic and simulation tools to estimate the minimum sample size required for achieving a target prediction mean-squared error (PMSE) or a specified proportional PMSE reduction (pPMSEr) in linear regression models. Functions implement the criteria of Ma (2023) <https://digital.wpi.edu/downloads/0g354j58c>, support covariance-matrix handling, and include helpers for root-finding and diagnostic plotting.
Version: | 0.1.1 |
Imports: | Matrix, stats, rootSolve |
Suggests: | rmarkdown, testthat (≥ 3.0.0) |
Published: | 2025-09-09 |
DOI: | 10.32614/CRAN.package.pmsesampling |
Author: | Louis Chen [aut, cre], Zheyang Wu [aut, ths] |
Maintainer: | Louis Chen <chenaters at gmail.com> |
BugReports: | https://github.com/Chenaters/pmsesampling/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/Chenaters/pmsesampling |
NeedsCompilation: | no |
CRAN checks: | pmsesampling results |
Reference manual: | pmsesampling.html , pmsesampling.pdf |
Package source: | pmsesampling_0.1.1.tar.gz |
Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
macOS binaries: | r-release (arm64): pmsesampling_0.1.1.tgz, r-oldrel (arm64): pmsesampling_0.1.1.tgz, r-release (x86_64): pmsesampling_0.1.1.tgz, r-oldrel (x86_64): pmsesampling_0.1.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=pmsesampling to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.