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Titlebook: Introduction to Optimization Methods and their Application in Statistics; B. S. Everitt Book 1987 B. S. Everitt 1987 applied statistics.cl

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發(fā)表于 2025-3-21 16:35:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Introduction to Optimization Methods and their Application in Statistics
編輯B. S. Everitt
視頻videohttp://file.papertrans.cn/475/474005/474005.mp4
圖書封面Titlebook: Introduction to Optimization Methods and their Application in Statistics;  B. S. Everitt Book 1987 B. S. Everitt 1987 applied statistics.cl
描述Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.
出版日期Book 1987
關(guān)鍵詞applied statistics; cluster analysis; factor analysis; fitting; generalized linear model; likelihood; line
版次1
doihttps://doi.org/10.1007/978-94-009-3153-4
isbn_softcover978-94-010-7917-4
isbn_ebook978-94-009-3153-4
copyrightB. S. Everitt 1987
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Some examples of the application of optimization techniques to statistical problems,In this chapter we shall illustrate the use of several of the minimization techniques discussed in Chapters 2 and 3 on a number of relatively straightforward statistical problems. In addition a number of optimization algorithms not previously described but which are of particular relevance in statistics will be mentioned.
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https://doi.org/10.1007/978-94-009-3153-4applied statistics; cluster analysis; factor analysis; fitting; generalized linear model; likelihood; line
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uch methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization tec
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