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 |