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| plsRglm-package | Partial least squares Regression for generalized linear models |
| aic.dof | Akaike and Bayesian Information Criteria and Generalized minimum description length |
| AICpls | AIC function for plsR models |
| aze | Microsat Dataset |
| aze_compl | As aze without missing values |
| 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 |
| boxplots.bootpls | Boxplot bootstrap distributions |
| coefs.plsR | Coefficients for bootstrap computations |
| coefs.plsRglm | Coefficients for bootstrap computations |
| confints.bootpls | Bootstrap confidence intervals |
| CorMat | Correlation matrix for simulating plsR datasets |
| Cornell | Cornell dataset |
| dicho | Dichotomization |
| fowlkes | Fowlkes dataset |
| gmdl.dof | Akaike and Bayesian Information Criteria and Generalized minimum description length |
| infcrit.dof | Information criteria |
| kfolds2Chisq | Computes Predicted Chisquare for kfold cross validated partial least squares regression models. |
| kfolds2Chisqind | Computes individual Predicted Chisquare for kfold cross validated partial least squares regression models. |
| kfolds2coeff | Extracts coefficients from kfold cross validated partial least squares regression models |
| kfolds2CVinfos_glm | Extracts and computes information criteria and fits statistics for kfold cross validated partial least squares glm models |
| kfolds2Mclassed | Number of missclassified individuals for kfold cross validated partial least squares regression models. |
| kfolds2Mclassedind | Number of missclassified individuals per group for kfold cross validated partial least squares regression models. |
| kfolds2Press | Computes PRESS for kfold cross validated partial least squares regression models. |
| kfolds2Pressind | Computes individual PRESS for kfold cross validated partial least squares regression models. |
| loglikpls | loglikelihood function for plsR models |
| permcoefs.plsR | Coefficients computation for permutation bootstrap |
| permcoefs.plsRglm | Coefficients computation for permutation bootstrap |
| pine | Pine dataset |
| pine_full | Full pine dataset |
| pine_sup | Supplementary data for pine dataset |
| 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 |
| 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 kfold cross validation |
| PLS_glm_kfoldcv_formula | Partial least squares regression glm models with kfold 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 kfold cross validation |
| PLS_lm_kfoldcv_formula | Partial least squares regression models with kfold cross validation |
| PLS_lm_wvc | Light version of PLS\_lm for cross validation purposes |
| 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 |
| simul_data_complete | Data generating detailed process for multivariate plsR models |
| simul_data_UniYX | Data generating function for univariate plsR models |
| simul_data_YX | Data generating function for multivariate plsR models |
| summary.plsRglmmodel | Summary method for plsRglm models |
| summary.plsRmodel | Summary method for plsR models |
| tilt.bootpls | Tilted bootstrap for PLS models |
| tilt.bootplsglm | Tilted bootstrap for PLS models |
| XbordeauxNA | Missing data analysis for the quality of wine dataset |
| XpineNAX21 | Missing data analysis for the pine dataset |