Package: pmsesampling 0.1.0

pmsesampling: Sample Size Determination for Accurate Predictive Linear Regression

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.

Authors:Louis Chen [aut, cre], Zheyang Wu [aut, ths]

pmsesampling_0.1.0.tar.gz
pmsesampling_0.1.0.zip(r-4.7)pmsesampling_0.1.0.zip(r-4.6)pmsesampling_0.1.0.zip(r-4.5)
pmsesampling_0.1.0.tgz(r-4.6-any)pmsesampling_0.1.0.tgz(r-4.5-any)
pmsesampling_0.1.0.tar.gz(r-4.7-any)pmsesampling_0.1.0.tar.gz(r-4.6-any)
pmsesampling_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
pmsesampling/json (API)

# Install 'pmsesampling' in R:
install.packages('pmsesampling', repos = c('https://chenaters.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chenaters/pmsesampling/issues

On CRAN:

Conda:

2.30 score 437 downloads 1 exports 3 dependencies

Last updated from:227902c54c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK123
source / vignettesOK169
linux-release-x86_64OK124
macos-release-arm64OK158
macos-oldrel-arm64OK136
windows-develOK79
windows-releaseOK78
windows-oldrelOK74
wasm-releaseOK106

Exports:pmse_samplesize

Dependencies:latticeMatrixrootSolve