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[下载] 【英美经典书籍】《Statistical Estimation: Asymptotic Theory》

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发表于 2017-1-3 20:17:16 | 显示全部楼层 |阅读模式
【英美经典书籍】《Statistical Estimation: Asymptotic Theory》
【英美经典书籍】《Statistical Estimation: Asymptotic Theory》【已搜索,无重复】

我上传的这本书:
作者:I.A. Ibragimov, R.Z. Has'minskii, S. Kotz
1981年,408 页,DJVU 格式,3 MB。
Language: English
.
封面:



简介:
when certain parameters in the problem tend to limiting values (for example, when the sample size increases indefinitely, the intensity of the noise ap- proaches zero, etc.) To address the problem of asymptotically optimal estimators consider the following important case. Let X 1, X 2, ... , X n be independent observations with the joint probability density !(x,O) (with respect to the Lebesgue measure on the real line) which depends on the unknown patameter o e 9 c R1. It is required to derive the best (asymptotically) estimator 0
X b ... , X n) of the parameter O. The first question which arises in connection with this problem is how to compare different estimators or, equivalently, how to assess their quality, in terms of the mean square deviation from the parameter or perhaps in some other way. The presently accepted approach to this problem, resulting from A. Wald's contributions, is as follows: introduce a nonnegative function w(0l> ( ), Ob Oe 9 (the loss function) and given two estimators Of and O! n 2 2 the estimator for which the expected loss (risk) Eown(Oj, 0), j = 1 or 2, is smallest is called the better with respect to Wn at point 0 (here EoO is the expectation evaluated under the assumption that the true value of the parameter is 0). Obviously, such a method of comparison is not without its defects.


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发表于 2017-1-16 18:45:26 | 显示全部楼层
{:4_100:}{:4_100:}{:4_100:}{:4_100:}{:4_100:}:niu:niu:niu:niu:niu
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发表于 2017-1-19 08:30:18 | 显示全部楼层
统计估值与渐进理论,看不懂题目哎,谢谢楼主分享,学习哈
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发表于 2017-2-28 15:09:18 | 显示全部楼层
谢谢分享
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