Monte Carlo Statistical Methods (Springer Texts in Statistics) pdf epub mobi txt 電子書 下載 2024


Monte Carlo Statistical Methods (Springer Texts in Statistics)

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Christian Robert
Springer
2004-07-28
649
USD 109.00
Hardcover
Springer Texts in Statistics
9780387212395

圖書標籤: statistics  Statistics  濛特卡羅  貝葉斯  課程教材  英文  統計  數學   


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发表于2024-11-10

Monte Carlo Statistical Methods (Springer Texts in Statistics) epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Monte Carlo Statistical Methods (Springer Texts in Statistics) epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Monte Carlo Statistical Methods (Springer Texts in Statistics) pdf epub mobi txt 電子書 下載 2024



圖書描述

Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at UniversitA(c) Paris Dauphine, France. He is also Head of the Statistics Laboratory at the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique. He has written three other books, including The Bayesian Choice, Second Edition, Springer 2001. He also edited Discretization and MCMC Convergence Assessment, Springer 1998. He has served as associate editor for the Annals of Statistics and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the SocietiA(c) de Statistique de Paris in 1995. George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association and Executive Editor of Statistical Science. He has authored three other textbooks: Statistical Inference, Second Edition, 2001, with Roger L. Berger; Theory of Point Estimation, 1998, with Erich Lehmann; and Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute.

Monte Carlo Statistical Methods (Springer Texts in Statistics) 下載 mobi epub pdf txt 電子書

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Monte Carlo Statistical Methods (Springer Texts in Statistics) pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

用戶評價

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讀後感

評分

当初决定做Monte Carlo,导师给我推荐了此书作为入门。 这本书是我所知道的Monte Carlo领域的几本好书之一(另一本在看的是Jun Liu写的)。本书内容包括Monte carlo领域从入门到精通的各个层次,正如其名,虽然Monte Carlo有着广泛的应用,但此书主要介绍其在统计学里面的应用...  

評分

当初决定做Monte Carlo,导师给我推荐了此书作为入门。 这本书是我所知道的Monte Carlo领域的几本好书之一(另一本在看的是Jun Liu写的)。本书内容包括Monte carlo领域从入门到精通的各个层次,正如其名,虽然Monte Carlo有着广泛的应用,但此书主要介绍其在统计学里面的应用...  

評分

当初决定做Monte Carlo,导师给我推荐了此书作为入门。 这本书是我所知道的Monte Carlo领域的几本好书之一(另一本在看的是Jun Liu写的)。本书内容包括Monte carlo领域从入门到精通的各个层次,正如其名,虽然Monte Carlo有着广泛的应用,但此书主要介绍其在统计学里面的应用...  

評分

当初决定做Monte Carlo,导师给我推荐了此书作为入门。 这本书是我所知道的Monte Carlo领域的几本好书之一(另一本在看的是Jun Liu写的)。本书内容包括Monte carlo领域从入门到精通的各个层次,正如其名,虽然Monte Carlo有着广泛的应用,但此书主要介绍其在统计学里面的应用...  

評分

知道这本书是某年在人大听Hong介绍的,那时还没接触过这方面的内容,一看作者,Robert之前看过他写过的关于Bayesian Statistics,Casella之前看过他和Lehmann合写的书,都素大师啊。找来看过后,两个字的感觉:过瘾。这本书比较适合有些贝叶斯基础和极限理论基础的读者吧应该。

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