# Partial Least Squares Regression for Generalized Linear Models

## Documentation for package ‘plsRglm’ version 1.7.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.
- Package NEWS.

## Help Pages

A B C D F G I K L P S T W X

## -- A --

aic.dof | Akaike and Bayesian Information Criteria and Generalized minimum description length
AICpls | AIC function for plsR models
aze | Microsatellites Dataset
aze_compl | As aze without missing values

## -- B --

bic.dof | Akaike and Bayesian Information Criteria and Generalized minimum description length
bootpls | Non-parametric Bootstrap for PLS models
bootplsglm | Non-parametric Bootstrap for PLS generalized linear models
bordeaux | Quality of wine dataset
bordeauxNA | Quality of wine dataset
boxplots.bootpls | Boxplot bootstrap distributions

## -- C --

classbiplot | Grouped biplot for PLS scores and loadings
coef.plsRglmmodel | coef method for plsR models
coef.plsRmodel | coef method for plsR models
coefs.plsR | Coefficients for bootstrap computations of PLSR models
coefs.plsR.raw | Raw coefficients for bootstrap computations of PLSR models
coefs.plsRglm | Coefficients for bootstrap computations of PLSGLR models
coefs.plsRglm.raw | Raw coefficients for bootstrap computations of PLSGLR models
coefs.plsRglmnp | Coefficients for bootstrap computations of PLSGLR models
coefs.plsRnp | Coefficients for bootstrap computations of PLSR models
confints.bootpls | Bootstrap confidence intervals
confints2signifind | Detect significant predictors from bootstrap confidence intervals
CorMat | Correlation matrix for simulating plsR datasets
Cornell | Cornell dataset
cv.plsR | Partial least squares regression models with k-fold cross-validation
cv.plsRglm | Partial least squares regression glm models with k-fold cross validation
cv.plsRglmmodel.default | Partial least squares regression glm models with k-fold cross validation
cv.plsRglmmodel.formula | Partial least squares regression glm models with k-fold cross validation
cv.plsRmodel.default | Partial least squares regression models with k-fold cross-validation
cv.plsRmodel.formula | Partial least squares regression models with k-fold cross-validation
cv.plsRmulti | Experimental k-fold cross-validation for multivariate-response PLS2
cv.plsRmultiModel | Experimental k-fold cross-validation for multivariate-response PLS2
cv.plsRmultiModel.default | Experimental k-fold cross-validation for multivariate-response PLS2
cv.plsRmultiModel.formula | Experimental k-fold cross-validation for multivariate-response PLS2
cvtable | Table method for summary of cross validated PLSR and PLSGLR models
cvtable.plsR | Table method for summary of cross validated PLSR and PLSGLR models
cvtable.plsRglm | Table method for summary of cross validated PLSR and PLSGLR models

## -- D --

dicho | Dichotomization

## -- F --

fowlkes | Fowlkes dataset

## -- G --

gmdl.dof | Akaike and Bayesian Information Criteria and Generalized minimum description length

## -- I --

infcrit.dof | Information criteria

## -- K --

kfolds2Chisq | Computes Predicted Chisquare for k-fold cross-validated partial least squares regression models.
kfolds2Chisqind | Computes individual Predicted Chisquare for k-fold cross validated partial least squares regression models.
kfolds2coeff | Extracts coefficients from 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
kfolds2CVinfos_lm | Extracts and computes information criteria and fits statistics for k-fold cross validated partial least squares models
kfolds2Mclassed | Number of missclassified individuals for k-fold cross validated partial least squares regression models.
kfolds2Mclassedind | Number of missclassified individuals per group for k-fold cross validated partial least squares regression models.
kfolds2Press | Computes PRESS for k-fold cross validated partial least squares regression models.
kfolds2Pressind | Computes individual PRESS for k-fold cross validated partial least squares regression models.

## -- L --

loglikpls | loglikelihood function for plsR models

## -- P --

permcoefs.plsR | Coefficients for permutation bootstrap computations of PLSR models
permcoefs.plsR.raw | Raw coefficients for permutation bootstrap computations of PLSR models
permcoefs.plsRglm | Coefficients for permutation bootstrap computations of PLSGLR models
permcoefs.plsRglm.raw | Raw coefficients for permutation bootstrap computations of PLSGLR models
permcoefs.plsRglmnp | Coefficients for permutation bootstrap computations of PLSGLR models
permcoefs.plsRnp | Coefficients computation for permutation bootstrap
pine | Pine dataset
pineNAX21 | Incomplete dataset from the pine caterpillars example
pine_full | Complete Pine dataset
pine_sup | Complete Pine dataset
plot.table.summary.cv.plsRglmmodel | Plot method for table of summary of cross validated plsRglm models
plot.table.summary.cv.plsRmodel | Plot method for table of summary of cross validated plsR models
plots.confints.bootpls | Plot bootstrap confidence intervals
plsR | Partial least squares Regression models with leave one out cross validation
plsR.dof | Computation of the Degrees of Freedom
plsRglm | Partial least squares Regression generalized linear models
plsRglmmodel.default | Partial least squares Regression generalized linear models
plsRglmmodel.formula | Partial least squares Regression generalized linear models
plsRmodel.default | Partial least squares Regression models with leave one out cross validation
plsRmodel.formula | Partial least squares Regression models with leave one out cross validation
plsRmulti | Experimental multivariate-response PLS2 models
plsRmultiModel | Experimental multivariate-response PLS2 models
plsRmultiModel.default | Experimental multivariate-response PLS2 models
plsRmultiModel.formula | Experimental multivariate-response PLS2 models
PLS_glm | Partial least squares Regression generalized linear models
PLS_glm_formula | Partial least squares Regression generalized linear models
PLS_glm_kfoldcv | Partial least squares regression glm models with k-fold cross validation
PLS_glm_kfoldcv_formula | Partial least squares regression glm models with k-fold cross validation
PLS_glm_wvc | Light version of PLS_glm for cross validation purposes
PLS_lm | Partial least squares Regression models with leave one out cross validation
PLS_lm_formula | Partial least squares Regression models with leave one out cross validation
PLS_lm_kfoldcv | Partial least squares regression models with k-fold cross-validation
PLS_lm_kfoldcv_formula | Partial least squares regression models with k-fold cross-validation
PLS_lm_wvc | Light version of PLS_lm for cross validation purposes
predict.plsRglmmodel | Print method for plsRglm models
predict.plsRmodel | Print method for plsR models
predict.plsRmultiModel | Predict method for experimental plsRmulti models
print.coef.plsRglmmodel | Print method for plsRglm models
print.coef.plsRmodel | Print method for plsR models
print.cv.plsRglmmodel | Print method for plsRglm models
print.cv.plsRmodel | Print method for plsR models
print.plsRglmmodel | Print method for plsRglm models
print.plsRmodel | Print method for plsR models
print.summary.plsRglmmodel | Print method for summaries of plsRglm models
print.summary.plsRmodel | Print method for summaries of plsR models

## -- S --

signpred | Graphical assessment of the stability of selected variables
simul_data_complete | Data generating detailed process for multivariate plsR models
simul_data_UniYX | Data generating function for univariate plsR models
simul_data_UniYX_binom | Data generating function for univariate binomial plsR models
simul_data_YX | Data generating function for multivariate plsR models
summary.cv.plsRglmmodel | Summary method for plsRglm models
summary.cv.plsRmodel | Summary method for plsR models
summary.cv.plsRmultiModel | Summary method for experimental multivariate PLS2 CV models
summary.plsRglmmodel | Summary method for plsRglm models
summary.plsRmodel | Summary method for plsR models

## -- T --

tilt.bootpls | Non-parametric tilted bootstrap for PLS regression models
tilt.bootplsglm | Non-parametric tilted bootstrap for PLS generalized linear regression models

## -- W --

weighted_significance | Compute cross-validation weighted significance scores

## -- X --

XbordeauxNA | Incomplete dataset for the quality of wine dataset
XpineNAX21 | Incomplete dataset from the pine caterpillars example