Package: EasyPCA 0.1.1
EasyPCA: Principal Component Analysis with Automated Interpretation and Visualization
Provides an automated workflow for Principal Component Analysis (PCA) that simplifies multivariate data analysis by performing essential preprocessing, statistical tests, component extraction, and visualization in a single function call. The package automatically standardizes variables, computes correlation matrices, performs Kaiser-Meyer-Olkin (KMO) and Bartlett's tests, determines the optimal number of principal components using multiple selection criteria, generates component loadings and scores, and produces publication-ready tables and graphical outputs for researchers and students. Methodological background is described in Shankar et al. (2024) <doi:10.1007/s12665-024-11985-5>.
Authors:
EasyPCA_0.1.1.tar.gz
EasyPCA_0.1.1.zip(r-4.7-any)EasyPCA_0.1.1.zip(r-4.6-any)EasyPCA_0.1.1.zip(r-4.5-any)
EasyPCA_0.1.1.tgz(r-4.6-any)EasyPCA_0.1.1.tgz(r-4.5-any)
EasyPCA_0.1.1.tar.gz(r-4.7-any)EasyPCA_0.1.1.tar.gz(r-4.6-any)
EasyPCA_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EasyPCA/json (API)
| # Install 'EasyPCA' in R: |
| install.packages('EasyPCA', repos = c('https://vishnumrstat.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:6cfa63e544. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 153 | ||
| source / vignettes | OK | 219 | ||
| linux-release | OK | 152 | ||
| macos-release | OK | 76 | ||
| macos-oldrel | OK | 96 | ||
| windows-devel | OK | 96 | ||
| windows-release | OK | 71 | ||
| windows-oldrel | OK | 60 | ||
| wasm-release | OK | 147 |
Exports:EasyPCA
Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecorrplotcowplotcpp11crosstalkdendextendDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluatefactoextraFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggcorrplotggplot2ggpubrggrepelggsciggsignifglueGPArotationgridExtragtablehighrhtmltoolshtmlwidgetsirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamnormtmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpbkrtestpillarpkgconfigplyrpolynompromisespsychpurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangrmarkdownrstatixS7sassscalesscatterplot3dshowtextshowtextdbSparseMstringistringrsurvivalsysfontstibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Principal Component Analysis with Automated Interpretation and Visualization | EasyPCA |
| Plot EasyPCA Results | plot.EasyPCA |