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plsRglm  

Partial Least Squares Regression for Generalized Linear Models
View on CRAN: Click here


Download and install plsRglm package within the R console
Install from CRAN:
install.packages("plsRglm")

Install from Github:
library("remotes")
install_github("cran/plsRglm")

Install by package version:
library("remotes")
install_version("plsRglm", "1.5.1")



Attach the package and use:
library("plsRglm")
Maintained by
Frederic Bertrand
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-09-20
Latest Update: 2023-03-14
Description:
Provides (weighted) Partial least squares Regression for generalized linear models and repeated 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.
How to cite:
Frederic Bertrand (2010). plsRglm: Partial Least Squares Regression for Generalized Linear Models. R package version 1.5.1, https://cran.r-project.org/web/packages/plsRglm. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.3.2 (2010-09-20 09:41), 0.3.3 (2010-10-05 10:24), 0.5.0 (2010-12-09 12:29), 0.6.3 (2011-01-09 09:45), 0.6.5 (2011-01-15 17:24), 0.7.0 (2011-03-29 08:55), 0.7.2 (2011-04-06 08:10), 0.7.4 (2011-04-11 08:36), 0.7.6 (2011-11-23 11:21), 0.7.9 (2012-08-27 09:02), 0.8.2 (2013-04-10 08:55), 0.8.3 (2014-03-10 07:58), 1.0.0 (2014-06-27 06:55), 1.0.1 (2014-06-28 18:53), 1.1.0 (2014-07-19 09:22), 1.1.1 (2014-12-17 02:20), 1.2.1 (2018-06-02 08:53), 1.2.3 (2018-06-11 23:12), 1.2.5 (2019-02-02 07:00), 1.3.0 (2021-03-15 23:40), 1.5.0 (2022-05-03 01:52)
Other packages that cited plsRglm R package
View plsRglm citation profile
Other R packages that plsRglm depends, imports, suggests or enhances
Complete documentation for plsRglm
Functions, R codes and Examples using the plsRglm R package
Some associated functions: AICpls . CorMat . Cornell . PLS_glm_wvc . PLS_lm_wvc . XbordeauxNA . XpineNAX21 . aic.dof . aze . aze_compl . bootpls . bootplsglm . bordeaux . bordeauxNA . boxplots.bootpls . coef.plsRglmmodel . coef.plsRmodel . coefs.plsR . coefs.plsR.raw . coefs.plsRglm . coefs.plsRglm.raw . coefs.plsRglmnp . coefs.plsRnp . confints.bootpls . cv.plsR . cv.plsRglm . cvtable . dicho . fowlkes . infcrit.dof . kfolds2CVinfos_glm . kfolds2CVinfos_lm . kfolds2Chisq . kfolds2Chisqind . kfolds2Mclassed . kfolds2Mclassedind . kfolds2Press . kfolds2Pressind . kfolds2coeff . loglikpls . permcoefs.plsR . permcoefs.plsR.raw . permcoefs.plsRglm . permcoefs.plsRglm.raw . permcoefs.plsRglmnp . permcoefs.plsRnp . pine . pineNAX21 . pine_full . pine_sup . plot.table.summary.cv.plsRglmmodel . plot.table.summary.cv.plsRmodel . plots.confints.bootpls . plsR.dof . plsR . plsRglm-package . plsRglm . predict.plsRglmmodel . predict.plsRmodel . print.coef.plsRglmmodel . print.coef.plsRmodel . print.cv.plsRglmmodel . print.cv.plsRmodel . print.plsRglmmodel . print.plsRmodel . print.summary.plsRglmmodel . print.summary.plsRmodel . signpred . simul_data_UniYX . simul_data_UniYX_binom . simul_data_YX . simul_data_complete . summary.cv.plsRglmmodel . summary.cv.plsRmodel . summary.plsRglmmodel . summary.plsRmodel . tilt.bootpls . tilt.bootplsglm . 
Some associated R codes: AICpls.R . PLS_glm.R . PLS_glm_formula.R . PLS_glm_kfoldcv.R . PLS_glm_kfoldcv_formula.R . PLS_glm_wvc.R . PLS_lm.R . PLS_lm_formula.R . PLS_lm_kfoldcv.R . PLS_lm_kfoldcv_formula.R . PLS_lm_wvc.R . aic.dof.R . bic.dof.R . bootpls.R . bootplsglm.R . boxplots.bootpls.R . coef.plsRglmmodel.R . coef.plsRmodel.R . coefs.plsR.R . coefs.plsR.raw.R . coefs.plsRglm.R . coefs.plsRglm.raw.R . coefs.plsRglmnp.R . confints.bootpls.R . cv.plsR.R . cv.plsRglm.R . cv.plsRglmmodel.default.R . cv.plsRglmmodel.formula.R . cv.plsRmodel.default.R . cv.plsRmodel.formula.R . cvtable.R . cvtable.plsR.R . cvtable.plsRglm.R . datasets.R . dicho.R . gmdl.dof.R . infcrit.dof.R . kfolds2CVinfos_glm.R . kfolds2CVinfos_lm.R . kfolds2Chisq.R . kfolds2Chisqind.R . kfolds2Mclassed.R . kfolds2Mclassedind.R . kfolds2Press.R . kfolds2Pressind.R . kfolds2coeff.R . loglikpls.R . permcoefs.plsR.R . permcoefs.plsR.raw.R . permcoefs.plsRglm.R . permcoefs.plsRglm.raw.R . permcoefs.plsRglmnp.R . permcoefs.plsRnp.R . plot.coef.plsRmodel.R . plot.table.summary.cv.plsRglmmodel.R . plot.table.summary.cv.plsRmodel.R . plots.confints.bootpls.R . plsR.R . plsR.dof.R . plsRglm-package.R . plsRglm.R . plsRglmmodel.default.R . plsRglmmodel.formula.R . plsRmodel.default.R . plsRmodel.formula.R . predict.plsRglmmodel.R . predict.plsRmodel.R . print.coef.plsRglmmodel.R . print.coef.plsRmodel.R . print.cv.plsRglmmodel.R . print.cv.plsRmodel.R . print.plsRglmmodel.R . print.plsRmodel.R . print.summary.plsRglmmodel.R . print.summary.plsRmodel.R . signpred.R . simul_data_UniYX.R . simul_data_UniYX_binom.R . simul_data_YX.R . simul_data_complete.R . summary.cv.plsRglmmodel.R . summary.cv.plsRmodel.R . summary.plsRglmmodel.R . summary.plsRmodel.R . tilt.bootpls.R . tilt.bootplsglm.R .  Full plsRglm package functions and examples
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