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powerPLS

This package provides a tool to perform power analysis in Partial Least Squares (PLS) for classification when two classes are analyzed.

Installation

You can install the released version of powerPLS with:

devtools::install_github("angeella/powerPLS")

Quick overview

The main functions are

  • computeSampleSize() which estimated the power considering several values of sample size and number of score components.

  • computePower() which estimated the power considering a fixed sample size and several number of score components.

datas <- simulatePilotData(nvar = 10, clus.size = c(5,5),m = 6,nvar_rel = 5,A = 2)
out <- computePower(X = datas$X, Y = datas$Y, A = 3, n = 20, test = "R2")
out <- computeSampleSize(X = datas$X, Y = datas$Y, A = 2, A = 3, n = 20, test = "R2")

References

Andreella, A., Finos, L., Scarpa, B. and Stocchero, M. "Towards a power analysis for PLS-based methods" arXiv:2403.10289 stat.ME. link: https://arxiv.org/abs/2403.10289

Did you find some bugs?

Please write to angela.andreella[\at]unitn[\dot]it or insert a reproducible example using reprex on my issue github page.

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Version

Install

install.packages('powerPLS')

Monthly Downloads

143

Version

0.2.1

License

GPL (>= 2)

Issues

Pull Requests

Stars

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Maintainer

Angela Andreella

Last Published

March 6th, 2025

Functions in powerPLS (0.2.1)

sensitivityTest

sensitivity test
simulatePilotData

Simulate pilot data
wheezing

Wheezing data
repeatedCV_test

Repeated k-Fold Cross-Validation with Custom Test Metrics
FMTest

FM test
PLSc

PLS classification
IDA

Iteration Deflation Algorithm
computePower

Power estimation
computeSampleSize

Sample size estimation
scoreTest

Score test
R2Test

R2 test
F1Test

F1 test
AUCTest

AUC test
sim_XY

Simulate pilot data
specificityTest

specificity test
aqueous_humour

Aqueous Humour data
computeWT

Compute weight and score matrices from PLSc
mccTest

MCC test
dQ2Test

dQ2 test
ptPLSc

post transformed PLS