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Titlebook: Statistical Estimation; Asymptotic Theory I. A. Ibragimov,R. Z. Has’minskii Book 1981 Springer Science+Business Media New York 1981 Asympto

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發(fā)表于 2025-3-21 20:08:16 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Statistical Estimation
副標(biāo)題Asymptotic Theory
編輯I. A. Ibragimov,R. Z. Has’minskii
視頻videohttp://file.papertrans.cn/877/876411/876411.mp4
叢書名稱Stochastic Modelling and Applied Probability
圖書封面Titlebook: Statistical Estimation; Asymptotic Theory I. A. Ibragimov,R. Z. Has’minskii Book 1981 Springer Science+Business Media New York 1981 Asympto
描述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 evalua
出版日期Book 1981
關(guān)鍵詞Asymptotische Wirksamkeit; Estimation Theory; Estimator; Parameter; Sch?tzung (Statistik)
版次1
doihttps://doi.org/10.1007/978-1-4899-0027-2
isbn_ebook978-1-4899-0027-2Series ISSN 0172-4568 Series E-ISSN 2197-439X
issn_series 0172-4568
copyrightSpringer Science+Business Media New York 1981
The information of publication is updating

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d. Chapter 9 is an introduction to weak formulations, Sobolev spaces, and direct variationalmethods for linear and quasi-linearelliptic equations. While terse, the material on Sobolev spaces is reasonably compl978-0-8176-4552-6Series ISSN 2197-182X Series E-ISSN 2197-1838
板凳
發(fā)表于 2025-3-22 03:47:14 | 只看該作者
I. A. Ibragimov,R. Z. Has’minskiid. Chapter 9 is an introduction to weak formulations, Sobolev spaces, and direct variationalmethods for linear and quasi-linearelliptic equations. While terse, the material on Sobolev spaces is reasonably compl978-0-8176-4552-6Series ISSN 2197-182X Series E-ISSN 2197-1838
地板
發(fā)表于 2025-3-22 07:17:00 | 只看該作者
I. A. Ibragimov,R. Z. Has’minskiid. Chapter 9 is an introduction to weak formulations, Sobolev spaces, and direct variationalmethods for linear and quasi-linearelliptic equations. While terse, the material on Sobolev spaces is reasonably compl978-0-8176-4552-6Series ISSN 2197-182X Series E-ISSN 2197-1838
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I. A. Ibragimov,R. Z. Has’minskiifinite difference and finite element methods. Computer-aided calculation with Maple? completes the book. Throughout, three fundamental examples are studied with different tools: Poisson’s equation, the heat equ978-3-031-13381-7978-3-031-13379-4Series ISSN 0072-5285 Series E-ISSN 2197-5612
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I. A. Ibragimov,R. Z. Has’minskiirical conditions on the graph of solutions, such as quasi-concavity, for uniqueness to hold. Chapter 9 is an introduction to weak formulations, Sobolev spaces, and direct variationalmethods for linear and quasi-linearelliptic equations. While terse, the material on Sobolev spaces is reasonably compl
9#
發(fā)表于 2025-3-23 04:37:06 | 只看該作者
Book 1981is 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 evalua
10#
發(fā)表于 2025-3-23 07:56:05 | 只看該作者
The Problem of Statistical Estimation,Observations constitute the basis of a statistical experiment: these may be numerical data or data of some other nature obtained as a result of a statistical experiment. The problem is to make, based on these data, some definite and sufficiently reliable conclusions concerning the object under investigation.
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