Titlebook: Shrinkage Estimation; Dominique Fourdrinier,William E. Strawderman,Marti Book 2018 Springer Nature Switzerland AG 2018 Minimax Estimation.

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书目名称Shrinkage Estimation影响因子(影响力)




书目名称Shrinkage Estimation影响因子(影响力)学科排名




书目名称Shrinkage Estimation网络公开度




书目名称Shrinkage Estimation网络公开度学科排名




书目名称Shrinkage Estimation被引频次




书目名称Shrinkage Estimation被引频次学科排名




书目名称Shrinkage Estimation年度引用




书目名称Shrinkage Estimation年度引用学科排名




书目名称Shrinkage Estimation读者反馈




书目名称Shrinkage Estimation读者反馈学科排名

才能

Meander

Decision Theory Preliminaries, sufficiency, completeness and unbiasedness at the level of, for example, Casella and Berger (.), Shao (.), or Bickel and Doksum (.). In the following, we will discuss, often without proof, some results in Bayesian decision theory, minimaxity, admissibility, invariance, and general linear models.

SOBER

grudging

大看台

COLIC

debase

Estimation of a Normal Mean Vector I,r will be concerned with the case of a known covariance matrix of the form . = .... and “usual quadratic loss,” .(., .) = ∥. − .∥. = (. − .).(. − .). Generalizations to known general covariance matrix ., and to general quadratic loss, .(., .) = (. − .)..(. − .), where . is a . × . symmetric non-nega

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Chameleon

Spherically Symmetric Distributions,tion vector could be improved upon quite generally for . ≥ 3 and Brown (.) substantially extended this conclusion to essentially arbitrary loss functions. Explicit results of the James-Stein type, however, have thus far been restricted to the case of the normal distribution. Recall the geometrical i