Minimax Multiple Shrinkage Estimation

By Edward I. George. 1986

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Citations in the corpus

Kernel Mean Shrinkage Estimators (2014, methodology): “ass For a subspace in the RKHS, as opposed to a single function f∗. This is particularly useful, for example, when we have vague or conﬂicting prior information about the true kernel mean. See, e.g., George (1986) and references therein for earlier researches in this direction. Secondly, we may use ”
General maximum likelihood empirical Bayes estimation of normal means (2009, background): “Moreover, if θi ∈B ∀i for a finite set B ⊂ R, the GMLEB adaptively shrinks toward the points in B [19].”
Exponential Screening and optimal rates of sparse estimation (2010, methodology): “bakov (2007, 2008, 2009, 2010) suggested several procedures of this kind based on continuous sparsity priors. Our approach is diﬀerent because we use a discrete prior in the spirit of earlier work by George (1986a,b); Leung and Barron (2006); Giraud (2008). Unlike George (1986a,b); Leung and Barron ”
Frequentist Model Average Estimators (2003, background): “As mentioned previously, the Bayesian literature so far decidedly outgoliaths its frequentist counterpart concerning model averaging inference and estimator postselection performance. Some work in the frequentist directions has, however, been done over the last decade. Hurvich and Tsai (1990) pointe”
Optimal Model Assessment, Selection, and Combination (2006, methodology): “For FMA, George (1986) constructed weights through multiple shrinkage, whereas Buckland, Burnham, and Augustin (1997) suggested that w(M) is proportional to an exponentiated negative AIC or BIC value at M. Yang (2001) used a split-sample method to determine model weights in linear regression. Hjort ”
Sharp Oracle Inequalities for Aggregation of Affine Estimators (2011, methodology): “In the framework of aggregating statistical procedures, the use of such an aggregate can be traced back to George [31].”
Multivariate Shrinkage for Optimal Portfolio Weights (2007, methodology): “One possible reason is the choice of implausible target portfolio weights c (George, 1986).”