Package: powerPLS 0.2.0

powerPLS: Power Analysis for PLS Classification

It estimates power and sample size for Partial Least Squares-based methods described in Andreella, et al., (2024), <doi:10.48550/arXiv.2403.10289>.

Authors:Angela Andreella [aut, cre]

powerPLS_0.2.0.tar.gz
powerPLS_0.2.0.zip(r-4.7-any)powerPLS_0.2.0.zip(r-4.6-any)powerPLS_0.2.0.zip(r-4.5-any)
powerPLS_0.2.0.tgz(r-4.6-any)powerPLS_0.2.0.tgz(r-4.5-any)
powerPLS_0.2.0.tar.gz(r-4.7-any)powerPLS_0.2.0.tar.gz(r-4.6-any)
powerPLS_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
powerPLS/json (API)

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

Bug tracker:https://github.com/angeella/powerpls/issues

Datasets:

On CRAN:

Conda:

2.70 score 202 downloads 18 exports 93 dependencies

Last updated from:966ae22238. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK188
source / vignettesOK281
linux-releaseOK193
macos-releaseOK128
macos-oldrelOK123
windows-develOK152
windows-releaseOK122
windows-oldrelOK113
wasm-releaseOK140

Exports:AUCTestcomputePowercomputeSampleSizecomputeWTdQ2TestF1TestFMTestIDAmccTestPLScptPLScR2TestrepeatedCV_testscoreTestsensitivityTestsim_XYsimulatePilotDataspecificityTest

Dependencies:bayesmcaretclasscliclockcodetoolscompositionscpp11data.tableDEoptimRdiagramdigestdplyre1071farverFKSUMFNNforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorskernlabKernSmoothkslabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmclustmgcvModelMetricsmulticoolmvtnormnipalsnlmennetnumDerivparallellypillarpkgconfigplyrpracmapROCprodlimprogressrproxypurrrR6rARPACKRColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrobustbaserpartRSpectraS7scalesshapesimukdesparsevctrsSQUAREMstringistringrsurvivaltensorAtibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr