Package: RXshrink
Title: Maximum Likelihood Shrinkage using Generalized Ridge or Least
Angle Regression Methods
Version: 1.4.3
Date: 2020-11-01
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob@att.net>
Depends: R (>= 3.5.0), lars, ellipse
Description: Functions are provided to calculate and display ridge TRACE diagnostics for
a variety of shrinkage Paths. TRACEs identify the m-Extent of shrinkage most likely,
under Normal-theory, to produce optimally biased estimates of beta-coefficients with
minimum MSE Risk. The unr.ridge() function implements the "Unrestricted Path"
introduced in Obenchain (2020) <arXiv:2005.14291>. This Shrinkage-Path is more
efficient than the Paths used by the qm.ridge(), aug.lars() and uc.lars() functions.
Optimally biased predictions can be made using RXpredict() for all six types of
RXshrink linear model estimation methods. Functions MLboot(), MLcalc(), MLhist() and
MLtrue() provide insights into the true bias and MSE risk characteristics of non-linear
Shrinkage estimators. Functions unr.aug() and unr.biv() augment the calculations made
by unr.ridge() to provide plots of the bivariate confidence ellipses corresponding to
any of the p*(p-1) possible pairs of shrunken regression coefficients. The correct.signs()
function provides estimates with "correct" numerical signs when ill-conditioned (nearly
multicollinear) models yield OLS estimates that disagree with the signs of the observed
correlations between the y-outcome and the selected x-predictor variables.
License: GPL-2
URL: https://www.R-project.org , http://localcontrolstatistics.org
NeedsCompilation: no
Packaged: 2020-10-30 01:06:18 UTC; bobo
Repository: CRAN
Date/Publication: 2020-11-01 13:30:02 UTC

Package: RXshrink
Title: Maximum Likelihood Shrinkage using Generalized Ridge or Least
Angle Regression Methods
Version: 1.4
Date: 2020-06-30
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob@att.net>
Depends: R (>= 3.5.0), lars
Description: Functions are provided to calculate and display ridge TRACEs for various
shrinkage Paths. They determine the m-Extent of shrinkage most likely, under
Normal-theory, to produce optimally biased estimates of regression beta-coefficients
with minimum MSE Risk. The new unr.ridge() function implements the "Unrestricted
Path" introduced in "Ridge TRACE Diagnostics" <arXiv:2005.14291>. This Path appears
more efficient than the Paths used by the qm.ridge(), aug.lars() and uc.lars()
functions. In-Sample predictions can be made using RXpredict() for all five types of
RXshrink linear model TRACE diagnostics. New functions MLboot(), MLcalc(), MLhist()
and MLtrue() provide insights into the true bias and MSE risk characteristics of
non-linear Shrinkage estimators. The correct.signs() function provides estimates
with "correct" numerical signs when ill-conditioned (nearly multicollinear) models
yield OLS estimates that disagree with the signs of the observed correlations
between the y-outcome and the selected x-predictor variables.
License: GPL-2
URL: https://www.R-project.org , http://localcontrolstatistics.org ,
http://arxiv.org/abs/2005.14291
NeedsCompilation: no
Packaged: 2020-06-26 19:13:48 UTC; bobo
Repository: CRAN
Date/Publication: 2020-06-26 19:40:08 UTC