plsRbeta: Partial Least Squares Regression for Beta Regression Models

Provides Partial least squares Regression for (weighted) beta regression models and 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.

Author
Frederic Bertrand <frederic.bertrand@math.unistra.fr>, Myriam Maumy-Bertrand <myriam.maumy-bertrand@math.unistra.fr>, Nicolas Meyer <Nicolas.Meyer@nmeyer@unistra.fr>.
Date of publication
2014-12-17 16:18:28
Maintainer
Frederic Bertrand <frederic.bertrand@math.unistra.fr>
License
GPL-3
Version
0.2.0
URLs

View on CRAN

Man pages

bootplsbeta
Non-parametric Bootstrap for PLS generalized linear models
coefs.plsRbeta
Coefficients for bootstrap computations
kfolds2Chisq
Computes Predicted Chisquare for kfold cross validated...
kfolds2Chisqind
Computes individual Predicted Chisquare for kfold cross...
kfolds2CVinfos_beta
Extracts and computes information criteria and fits...
permcoefs.plsRbeta
Coefficients computation for permutation bootstrap
PLS_beta
Partial least squares Regression generalized linear models
PLS_beta_formula
Partial least squares Regression generalized linear models
PLS_beta_kfoldcv
Partial least squares regression beta models with kfold cross...
PLS_beta_kfoldcv_formula
Partial least squares regression beta models with kfold cross...
PLS_beta_wvc
Light version of PLS\_beta for cross validation purposes
plsRbeta
Partial least squares Regression generalized linear models
print.plsRbetamodel
Print method for plsRbeta models
print.summary.plsRbetamodel
Print method for summaries of plsRbeta models
simul_data_UniYX_beta
Data generating function for univariate beta plsR models
summary.plsRbetamodel
Summary method for plsRbeta models
tilt.bootplsbeta
Tilted bootstrap for PLS models

Files in this package

plsRbeta
plsRbeta/inst
plsRbeta/inst/CITATION
plsRbeta/NAMESPACE
plsRbeta/NEWS
plsRbeta/R
plsRbeta/R/PLS_beta_wvc.R
plsRbeta/R/PLS_beta_formula.R
plsRbeta/R/print.plsRbetamodel.R
plsRbeta/R/print.summary.plsRbetamodel.R
plsRbeta/R/plsRbetamodel.formula.R
plsRbeta/R/PLS_beta_kfoldcv_formula.R
plsRbeta/R/kfolds2CVinfos_beta.R
plsRbeta/R/permcoefs.plsRbeta.R
plsRbeta/R/kfolds2Chisqind.R
plsRbeta/R/kfolds2Chisq.R
plsRbeta/R/PLS_beta_kfoldcv.R
plsRbeta/R/bootplsbeta.R
plsRbeta/R/simul_data_UniYX_beta.R
plsRbeta/R/plsRbeta.R
plsRbeta/R/summary.plsRbetamodel.R
plsRbeta/R/PLS_beta.R
plsRbeta/R/tilt.bootplsbeta.R
plsRbeta/R/coefs.plsRbeta.R
plsRbeta/R/plsRbetamodel.default.R
plsRbeta/MD5
plsRbeta/DESCRIPTION
plsRbeta/man
plsRbeta/man/print.plsRbetamodel.Rd
plsRbeta/man/PLS_beta_kfoldcv_formula.Rd
plsRbeta/man/simul_data_UniYX_beta.Rd
plsRbeta/man/tilt.bootplsbeta.Rd
plsRbeta/man/coefs.plsRbeta.Rd
plsRbeta/man/kfolds2Chisq.Rd
plsRbeta/man/plsRbeta.Rd
plsRbeta/man/PLS_beta_wvc.Rd
plsRbeta/man/permcoefs.plsRbeta.Rd
plsRbeta/man/PLS_beta_formula.Rd
plsRbeta/man/bootplsbeta.Rd
plsRbeta/man/summary.plsRbetamodel.Rd
plsRbeta/man/print.summary.plsRbetamodel.Rd
plsRbeta/man/kfolds2CVinfos_beta.Rd
plsRbeta/man/PLS_beta_kfoldcv.Rd
plsRbeta/man/kfolds2Chisqind.Rd
plsRbeta/man/PLS_beta.Rd