varEst-package {varEst}

Variance Estimation

Description

Error variance estimation in ultrahigh dimensional datasets with four different methods, viz. Refitted cross validation, k-fold refitted cross validation, Bootstrap-refitted cross validation, Ensemble method.

Details

The DESCRIPTION file:

Package:	varEst
Type:	Package
Title:	Variance Estimation
Version:	0.1.0
Author:	Sayanti Guha Majumdar, Anil Rai, Dwijesh Chandra Mishra
Maintainer:	Sayanti Guha Majumdar <[e-mail]>
Description:	Error variance estimation in ultrahigh dimensional datasets with four different methods, viz. Refitted cross validation, k-fold refitted cross validation, Bootstrap-refitted cross validation, Ensemble method.
License:	GPL-3
Encoding:	UTF-8
LazyData:	TRUE
Imports:	SAM, caret, lm.beta, glmnet
RoxygenNote:	6.1.1

Index of help topics:

bsrcv                   Variance Estimation with Bootstrap-RCV
ensemble                Variance Estimation with Ensemble method
krcv                    Variance Estimation with kfold-RCV
rcv                     Variance Estimation with Refitted Cross
                        Validation(RCV)
varEst-package          Variance Estimation

Author(s)

Sayanti Guha Majumdar, Anil Rai, Dwijesh Chandra Mishra

Maintainer: Sayanti Guha Majumdar <[e-mail]>

References

Fan, J., Guo, S., Hao, N. (2012).Variance estimation using refitted cross-validation in ultrahigh dimensional regression. Journal of the Royal Statistical Society, 74(1), 37-65
Ravikumar, P., Lafferty, J., Liu, H. and Wasserman, L. (2009). Sparse additive models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 71(5), 1009-1030
Tibshirani, R. (1996). Regression shrinkage and selection via the Lasso. Journal of Royal Statistical Society, 58, 267-288