Learn R Programming

lsplsGlm (version 1.0)

Classification using LS-PLS for Logistic Regression

Description

Fit logistic regression models using LS-PLS approaches to analyse both clinical and genomic data. (C. Bazzoli and S. Lambert-Lacroix. (2017) Classification using LS-PLS with logistic regression based on both clinical and gene expression variables ).

Copy Link

Version

Install

install.packages('lsplsGlm')

Monthly Downloads

14

Version

1.0

License

GPL (>= 2)

Maintainer

Bazzoli Caroline

Last Published

July 27th, 2017

Functions in lsplsGlm (1.0)

BreastCancer

Gene expression and clinical data used to predict the presence of subclinical metastases for breast cancer patients
CentralCNS

Gene expression and clinical data used to predict tumors of Central Nervous System from children
SIS.selection

Sure Independence Screening
cv.lspcr.glm

Cross-validation for LS-PCR model for logistic regression
pls

Weighted PLS gaussian regression
predict.lspcr.glm

Predict method for LS-PCR fits.
predict.lspls.glm

Predict method for LS-PLS model fits.
preselected.sample

Selected randomized controlled random sample
cv.lspls.glm

Cross-validation for LS-PLS model for logistic regression
fit.lspcr.glm

Fitting a LS-PCR model for logistic regression
fit.lspls.glm

Fitting LS-PLS for generalized model for logistic regression
lspls

Weighted LS-PLS gaussian regression