BootValidation (0.1.3)

0 users

Adjusting for Optimism in 'glmnet' Regression using Bootstrapping.

Main objective of a predictive model is to provide accurated predictions of a new observations. Unfortunately we don't know how well the model performs. In addition, at the current era of omic data where p >> n, is not reasonable applying internal validation using data-splitting. Under this background a good method to assessing model performance is applying internal bootstrap validation (Harrell Jr, Frank E (2015) .) This package provides bootstrap validation for the linear and logistic 'glmnet' models.

Maintainer: Antonio Jose Canada Martinez
Author(s): Antonio Jose Canada Martinez

License: GPL (>= 2)

Uses: glmnet, pbapply, pROC

Released 4 months ago.



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of BootValidation yet. Want to be the first? Write one now.

Related packages:(20 best matches, based on common tags.)

Search for BootValidation on google, google scholar, r-help, r-devel.

Visit BootValidation on R Graphical Manual.