Package: folda 0.2.0.9000
folda: Forward Stepwise Discriminant Analysis with Pillai's Trace
A novel forward stepwise discriminant analysis framework that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA), providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda. A stand-alone ULDA implementation is also provided, offering a more general solution than the one available in the 'MASS' package. It automatically handles missing values and provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.
Authors:
folda_0.2.0.9000.tar.gz
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folda.pdf |folda.html✨
folda/json (API)
NEWS
# Install 'folda' in R: |
install.packages('folda', repos = c('https://moran79.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/moran79/folda/issues
Last updated 24 days agofrom:71875de6b7. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win-x86_64 | OK | Oct 30 2024 |
R-4.5-linux-x86_64 | OK | Oct 30 2024 |
R-4.4-win-x86_64 | OK | Oct 30 2024 |
R-4.4-mac-x86_64 | OK | Oct 30 2024 |
R-4.4-mac-aarch64 | OK | Oct 30 2024 |
R-4.3-win-x86_64 | OK | Oct 30 2024 |
R-4.3-mac-x86_64 | OK | Oct 30 2024 |
R-4.3-mac-aarch64 | OK | Oct 30 2024 |
Exports:checkPriorAndMisClassCostfoldagetChiSqStatgetDataInShapegetModemissingFix
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppEigenrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Check and Normalize Prior Probabilities and Misclassification Costs | checkPriorAndMisClassCost |
Forward Uncorrelated Linear Discriminant Analysis | folda |
Compute Chi-Squared Statistics for Variables | getChiSqStat |
Align Data with a Missing Reference | getDataInShape |
Calculate the Mode of a Factor Variable with Optional Priors | getMode |
Impute Missing Values and Add Missing Flags to a Data Frame | missingFix |
Plot Decision Boundaries and Linear Discriminant Scores | plot.ULDA |
Predict Method for ULDA Model | predict.ULDA |