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plsRglm (version 1.5.1)

Partial Least Squares Regression for Generalized Linear Models

Description

Provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria . It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.

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Version

Install

install.packages('plsRglm')

Monthly Downloads

1,006

Version

1.5.1

License

GPL-3

Issues

Pull Requests

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Repository

https://github.com/fbertran/plsRglm/

Homepage

https://fbertran.github.io/plsRglm/

Maintainer

Frederic Bertrand

Last Published

March 14th, 2023

Functions in plsRglm (1.5.1)

Correlation matrix for simulating plsR datasets

Incomplete dataset from the pine caterpillars example

As aze without missing values

Cornell dataset

Microsatellites Dataset

Akaike and Bayesian Information Criteria and Generalized minimum description length

Light version of PLS_glm for cross validation purposes

Light version of PLS_lm for cross validation purposes

AIC function for plsR models

Incomplete dataset for the quality of wine dataset

Raw coefficients for bootstrap computations of PLSR models

boxplots.bootpls

Boxplot bootstrap distributions

Non-parametric Bootstrap for PLS generalized linear models

Non-parametric Bootstrap for PLS models

Coefficients for bootstrap computations of PLSGLR models

coef.plsRglmmodel

coef method for plsR models

coef method for plsR models

Coefficients for bootstrap computations of PLSR models

Quality of wine dataset

Quality of wine dataset

Table method for summary of cross validated PLSR and PLSGLR models

coefs.plsRglm.raw

Raw coefficients for bootstrap computations of PLSGLR models

Coefficients for bootstrap computations of PLSR models

Partial least squares regression models with k-fold cross-validation

confints.bootpls

Bootstrap confidence intervals

Dichotomization

Fowlkes dataset

coefs.plsRglmnp

Coefficients for bootstrap computations of PLSGLR models

Partial least squares regression glm models with k-fold cross validation

Computes Predicted Chisquare for k-fold cross-validated partial least squares regression models.

kfolds2Mclassed

Number of missclassified individuals for k-fold cross validated partial least squares regression models.

kfolds2CVinfos_glm

Extracts and computes information criteria and fits statistics for k-fold cross validated partial least squares glm models

Information criteria

kfolds2CVinfos_lm

Extracts and computes information criteria and fits statistics for k-fold cross validated partial least squares models

kfolds2Chisqind

Computes individual Predicted Chisquare for k-fold cross validated partial least squares regression models.

Coefficients for permutation bootstrap computations of PLSR models

Incomplete dataset from the pine caterpillars example

permcoefs.plsR.raw

Raw coefficients for permutation bootstrap computations of PLSR models

kfolds2Mclassedind

Number of missclassified individuals per group for k-fold cross validated partial least squares regression models.

permcoefs.plsRglmnp

Coefficients for permutation bootstrap computations of PLSGLR models

Extracts coefficients from k-fold cross validated partial least squares regression models

permcoefs.plsRnp

Coefficients computation for permutation bootstrap

Complete Pine dataset

loglikelihood function for plsR models

Computes PRESS for k-fold cross validated partial least squares regression models.

predict.plsRmodel

Print method for plsR models

permcoefs.plsRglm.raw

Raw coefficients for permutation bootstrap computations of PLSGLR models

kfolds2Pressind

Computes individual PRESS for k-fold cross validated partial least squares regression models.

Complete Pine dataset

print.plsRmodel

Print method for plsR models

print.summary.plsRglmmodel

Print method for summaries of plsRglm models

print.coef.plsRglmmodel

Print method for plsRglm models

Graphical assessment of the stability of selected variables

permcoefs.plsRglm

Coefficients for permutation bootstrap computations of PLSGLR models

print.summary.plsRmodel

Print method for summaries of plsR models

simul_data_complete

Data generating detailed process for multivariate plsR models

plot.table.summary.cv.plsRglmmodel

Plot method for table of summary of cross validated plsRglm models

tilt.bootplsglm

Non-parametric tilted bootstrap for PLS generalized linear regression models

plot.table.summary.cv.plsRmodel

Plot method for table of summary of cross validated plsR models

Non-parametric tilted bootstrap for PLS regression models

Partial least squares Regression generalized linear models

predict.plsRglmmodel

Print method for plsRglm models

simul_data_UniYX

Data generating function for univariate plsR models

Partial least squares Regression models with leave one out cross validation

plots.confints.bootpls

Plot bootstrap confidence intervals

print.plsRglmmodel

Print method for plsRglm models

summary.plsRglmmodel

Summary method for plsRglm models

simul_data_UniYX_binom

Data generating function for univariate binomial plsR models

summary.cv.plsRmodel

Summary method for plsR models

Computation of the Degrees of Freedom

print.cv.plsRglmmodel

Print method for plsRglm models

summary.plsRmodel

Summary method for plsR models

plsRglm-package

plsRglm-package

print.coef.plsRmodel

Print method for plsR models

print.cv.plsRmodel

Print method for plsR models

summary.cv.plsRglmmodel

Summary method for plsRglm models

Data generating function for multivariate plsR models