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.

Install the latest version of this package by entering the following in R:
install.packages("plsRbeta")
AuthorFrederic Bertrand <frederic.bertrand@math.unistra.fr>, Myriam Maumy-Bertrand <myriam.maumy-bertrand@math.unistra.fr>, Nicolas Meyer <Nicolas.Meyer@nmeyer@unistra.fr>.
Date of publication2014-12-17 16:18:28
MaintainerFrederic Bertrand <frederic.bertrand@math.unistra.fr>
LicenseGPL-3
Version0.2.0
http://www-irma.u-strasbg.fr/~fbertran/

View on CRAN

Functions

bootplsbeta Man page
coefs.plsRbeta Man page
kfolds2Chisq Man page
kfolds2Chisqind Man page
kfolds2CVinfos_beta Man page
permcoefs.plsRbeta Man page
PLS_beta Man page
PLS_beta_formula Man page
PLS_beta_kfoldcv Man page
PLS_beta_kfoldcv_formula Man page
PLS_beta_wvc Man page
plsRbeta Man page
plsRbetamodel.default Man page
plsRbetamodel.formula Man page
print.plsRbetamodel Man page
print.summary.plsRbetamodel Man page
simul_data_UniYX_beta Man page
summary.plsRbetamodel Man page
tilt.bootplsbeta Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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