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.

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.

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