reams: Resampling-Based Adaptive Model Selection
Version 0.1

Resampling methods for adaptive linear model selection. These can be thought of as extensions of the Akaike information criterion that account for searching among candidate models.

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AuthorPhilip Reiss <phil.reiss@nyumc.org> and Lei Huang <huangracer@gmail.com>
Date of publication2012-10-29 08:59:35
MaintainerTao Zhang <tao-zhang-1@uiowa.edu>
LicenseGPL (>= 2)
Version0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("reams")

Man pages

bestmods: Find best submodels of a full linear model
cic: Covariance inflation criterion
cvic: Cross-validation information criterion
eic: Extended (bootstrap) information criterion
ic.min: AIC, corrected AIC and BIC for all-subsets linear regression
reams-package: Resampling-based adaptive model selection
scoremods: Score best subsets by information criteria
xy: Random generation of linear model matrix and outcomes

Functions

bestmods Man page Source code
cic Man page Source code
cvic Man page Source code
eic Man page Source code
ic.min Man page Source code
reams Man page
reams-package Man page
scoremods Man page Source code
xy Man page Source code

Files

devel
devel/plural.r
devel/plursim.R
devel/plursim.Rd
NAMESPACE
man
man/ic.min.Rd
man/scoremods.Rd
man/cvic.Rd
man/cic.Rd
man/bestmods.Rd
man/eic.Rd
man/xy.Rd
man/reams-package.Rd
DESCRIPTION
MD5
R
R/scoremods.R
R/ic.min.R
R/eic.R
R/cic.R
R/cvic.R
R/xy.R
R/bestmods.R
reams documentation built on May 20, 2017, 3:18 a.m.