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Wenjiang's thesis under Rob Tibshani at the University of Toronto is entitled "A Statistical Shrinkage Model and Its Applications."
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Nash reviewed PC software that included softRX freeware stand-alone (DOS) applications.
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Ordinary least squares and diagonally-weighted least squares always produce residuals that are optimal estimators of lack-of-fit ...even when the expectation model and/or dispersion model you have specified are/is wrong!
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Classical, normal-theory monitoring of the likelihood-of-MSE-optimality along ANY shrinkage path.
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See this paper and/or my Frequently-Asked-Questions page for information on confidence intervals in shrinkage regression.
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The "ridge-function" theorem; maximum likelihood estimation of the "inferior direction" and of scaled MSE risk along any direction in p-dimensional regression coefficient space; MSE risk optimality of 0 or X'y along directions orthogonal to or parallel to beta, respectively.
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Proceedings of the Fordham Ridge Symposium, ed. H. D. Vinod; illustrations of usage of RXridge SAS/IML freeware.
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Introduction to basic shrinkage/ridge concepts; illustrations of usage of RXridge .ADO freeware.
Obenchain, R. L. (1995-2004). Shrinkage Regression: ridge, BLUP, Bayes and Stein. Unfinished eBook draft (185 pages.)
Obenchain, R. L. (2005-2021). RXshrink: an R-package for maximum likelihood shrinkage using generalized ridge or least angle regression, ver 2.0. CRAN.R-project.org And...View or Download vignette-like PDF
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