HAVEN
发表于 2025-3-21 19:56:15
书目名称Shrinkage Estimation影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0866783<br><br> <br><br>书目名称Shrinkage Estimation读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0866783<br><br> <br><br>
才能
发表于 2025-3-21 20:27:39
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Meander
发表于 2025-3-22 02:44:05
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
发表于 2025-3-22 06:11:22
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grudging
发表于 2025-3-22 10:03:07
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大看台
发表于 2025-3-22 13:25:01
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COLIC
发表于 2025-3-22 17:40:43
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debase
发表于 2025-3-22 23:47:52
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
偏见
发表于 2025-3-23 05:05:08
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Chameleon
发表于 2025-3-23 06:50:14
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