Partial Least Squares Regression for Generalized Linear Models
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Documentation for package ‘plsRglm’ version 1.5.1
- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.
- Package NEWS.
Help Pages
| plsRglm-package | plsRglm-package |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 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. |
| loglikpls | loglikelihood function for plsR models |
| 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 |
| 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 |
| 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 |
| 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.plsRglmmodel | Summary method for plsRglm models |
| summary.plsRmodel | Summary method for plsR models |
| tilt.bootpls | Non-parametric tilted bootstrap for PLS regression models |
| tilt.bootplsglm | Non-parametric tilted bootstrap for PLS generalized linear regression models |
| XbordeauxNA | Incomplete dataset for the quality of wine dataset |
| XpineNAX21 | Incomplete dataset from the pine caterpillars example |