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RXshrink (version 1.6)
Maximum Likelihood Shrinkage using Generalized Ridge or Least
Angle Regression Methods
Description
Functions are provided to calculate and display ridge TRACE diagnostics for a
wide variety of alternative shrinkage Paths. While all methods focus on Maximum Likelihood
estimation of unknown true effects under Normal-distribution theory, some estimates are
modified to be Unbiased or to have "Correct Range" when estimating either [1] the noncentrality
of the F-ratio for testing that true Beta coefficients are Zeros or [2] the "relative" MSE
Risk (i.e. MSE divided by true sigma-square, where the "relative" variance of OLS is known.)
The unr.ridge() function implements the "Unrestricted Path" introduced in Obenchain (2020)
. This "new" p-parameter Shrinkage-Path is more efficient than the Paths
used by qm.ridge(), aug.lars() and uc.lars(). 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.