[好书推荐] (原版丛书) Wiley Series in Probability and Statistics 49本(10.19更新) - 第7页

ssningok

2009-10-3 07:59:56

太好了，先收藏，有需要再下。谢谢！

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woshichaoji

2009-10-3 18:30:02

先收藏，以後再下載！
多謝樓主分享寶貴資料！有助於瞭解人類創造的動力！
本文来自: 人大经济论坛详细出处参考：http://www.pinggu.org/bbs/viewth ... amp;from^^uid=1170104

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chewweiw

2009-10-3 18:36:30

大好人thanks!

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damichong

2009-10-6 12:46:59

觉得把LZ的珍藏一本一本啃下来。

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damichong

2009-10-6 12:47:34

决定把LZ的珍藏一本一本啃下来。

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陌离

2009-10-9 04:04:39

经典从书，一定得收藏的

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qing2000

2009-10-9 08:47:48

非常好的资源！！！

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gooddrug

2009-10-9 14:59:52

太强悍了，赞赞！！！正在找Statistical Analysis With Missing Data，感谢楼主啊！！

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gooddrug

2009-10-9 15:02:38

太强悍了，赞赞！！！正在找Statistical Analysis With Missing Data，感谢楼主啊！！

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divergent

2009-10-11 13:41:43

Thank you very much~~ so many useful book! nice work!!

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huntaway

2009-10-14 16:39:24

25. Theory of Preliminary Test and Stein-Type Estimation with Applications
Theory of Preliminary Test and Stein-Type Estimation with Applications (Wiley Series in Probability and Statistics)
By A. K. Md. Ehsanes Saleh
Publisher: Wiley-Interscience
Number Of Pages: 656
Publication Date: 2006-03-27
ISBN-10 / ASIN: 0471563757
ISBN-13 / EAN: 9780471563754
Binding: Hardcover
Book Description:
Theory of Preliminary Test and Stein-Type Estimation with Applications provides a com-prehensive account of the theory and methods of estimation in a variety of standard models used in applied statistical inference. It is an in-depth introduction to the estimation theory for graduate students, practitioners, and researchers in various fields, such as statistics, engineering, social sciences, and medical sciences. Coverage of the material is designed as a first step in improving the estimates before applying full Bayesian methodology, while problems at the end of each chapter enlarge the scope of the applications.
This book contains clear and detailed coverage of basic terminology related to various topics, including:
* Simple linear model; ANOVA; parallelism model; multiple regression model with non-stochastic and stochastic constraints; regression with autocorrelated errors; ridge regression; and multivariate and discrete data models
* Normal, non-normal, and nonparametric theory of estimation
* Bayes and empirical Bayes methods
* R-estimation and U-statistics
* Confidence set estimation

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(25) Theory of Preliminary Test and Stein-Type Estimation with Applications.pdf

大小:22.06 MB

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huntaway

2009-10-14 16:57:59

26. The EM Algorithm and Extensions
The EM Algorithm and Extensions (Wiley Series in Probability and Statistics)
By Geoffrey J. McLachlan, Thriyambakam Krishnan
Publisher: Wiley-Interscience
Number Of Pages: 360
Publication Date: 2008-03-14
ISBN-10 / ASIN: 0471201707
ISBN-13 / EAN: 9780471201700
Book Description:
The EM Algorithm and Extensions remains the only single source to offer a complete and unified treatment of the theory, methodology, and applications of the EM algorithm. The highly applied area of statistics here outlined involves applications in regression, medical imaging, finite mixture analysis, robust statistical modeling, survival analysis, and repeated-measures designs, among other areas. The text includes newly added and updated results on convergence, and new discussion of categorical data, numerical differentiation, and variants of the EM algorithm. It also explores the relationship between the EM algorithm and the Gibbs sampler and Markov Chain Monte Carlo methods.

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(26) The EM Algorithm and Extensions.pdf

大小:17.67 MB

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covantaenergy

2009-10-15 09:32:34

多谢楼主,收藏了

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huntaway

2009-10-19 13:30:57

27. The Theory of Response-Adaptive Randomization in Clinical Trials
The Theory of Response-Adaptive Randomization in Clinical Trials (Wiley Series in Probability and Statistics)
By Feifang Hu, William F. Rosenberger
Publisher: Wiley-Interscience
Number Of Pages: 232
Publication Date: 2006-08-18
ISBN-10 / ASIN: 0471653969
ISBN-13 / EAN: 9780471653967
Product Description:
Presents a firm mathematical basis for the use of response-adaptive randomization procedures in practice
The Theory of Response-Adaptive Randomization in Clinical Trials is the result of the authors' ten-year collaboration as well as their collaborations with other researchers in investigating the important questions regarding response-adaptive randomization in a rigorous mathematical framework. Response-adaptive allocation has a long history in biostatistics literature; however, largely due to the disastrous ECMO trial in the early 1980s, there is a general reluctance to use these procedures.
This timely book represents a mathematically rigorous subdiscipline of experimental design involving randomization and answers fundamental questions, including:
How does response-adaptive randomization affect power?
Can standard inferential tests be applied following response-adaptive randomization?
What is the effect of delayed response?
Which procedure is most appropriate and how can "most appropriate" be quantified?
How can heterogeneity of the patient population be incorporated?
Can response-adaptive randomization be performed with more than two treatments or with continuous responses?
The answers to these questions communicate a thorough understanding of the asymptotic properties of each procedure discussed, including asymptotic normality, consistency, and asymptotic variance of the induced allocation. Topical coverage includes:
The relationship between power and response-adaptive randomization
The general result for determining asymptotically best procedures
Procedures based on urn models
Procedures based on sequential estimation
Implications for the practice of clinical trials
Useful for graduate students in mathematics, statistics, and biostatistics as well as researchers and industrial and academic biostatisticians, this book offers a rigorous treatment of the subject in order to find the optimal procedure to use in practice.

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(27) The Theory of Response-Adaptive Randomization in Clinical Trials.pdf

大小:8.15 MB

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huntaway

2009-10-19 13:36:13

30. Structural Equation Modelling: A Bayesian Approach
Structural Equation Modelling: A Bayesian Approach (Wiley Series in Probability and Statistics)
By Sik-Yum Lee
Publisher: Wiley
Number Of Pages: 458
Publication Date: 2007-03-23
ISBN-10 / ASIN: 0470024232
ISBN-13 / EAN: 9780470024232
Book Description:
Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples.
Structural Equation Modeling introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances.
Demonstrates how to utilize powerful statistical computing tools, including the Gibbs sampler, the Metropolis-Hasting algorithm, bridge sampling and path sampling to obtain the Bayesian results.
Discusses the Bayes factor and Deviance Information Criterion (DIC) for model comparison.
Includes coverage of complex models, including SEMs with ordered categorical variables, and dichotomous variables, nonlinear SEMs, two-level SEMs, multisample SEMs, mixtures of SEMs, SEMs with missing data, SEMs with variables from an exponential family of distributions, and some of their combinations.
Illustrates the methodology through simulation studies and examples with real data from business management, education, psychology, public health and sociology.
Demonstrates the application of the freely available software WinBUGS via a supplementary website featuring computer code and data sets.
Structural Equation Modeling: A Bayesian Approach is a multi-disciplinary text ideal for researchers and students in many areas, including: statistics, biostatistics, business, education, medicine, psychology, public health and social science.

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(30) Structural Equation Modelling, A Bayesian Approach.pdf

大小:8.47 MB

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huntaway

2009-10-19 13:38:09

31. Bootstrap Methods: A Guide for Practitioners and Researchers
Bootstrap Methods: A Guide for Practitioners and Researchers (Wiley Series in Probability and Statistics)
By Michael R. Chernick
Publisher: Wiley-Interscience
Number Of Pages: 369
Publication Date: 2007-11-12
ISBN-10 / ASIN: 0471756210
ISBN-13 / EAN: 9780471756217
Book Description:
This book provides an introduction to the bootstrap, offering reliable, authoritative coverage of the bootstrap's considerable advantages--as well as its drawbacks. This Second Edition takes great care to draw connections between the more traditional resampling methods and the bootstrap and places even more emphasis on the use of the bootstrap as an exploratory tool.

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(31) Bootstrap Methods, A Guide for Practitioners and Researchers.pdf

大小:2.28 MB

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huntaway

2009-10-19 13:44:19

32. Nonparametric Analysis of Univariate Heavy-Tailed Data: Research and Practice
Nonparametric Analysis of Univariate Heavy-Tailed Data: Research and Practice (Wiley Series in Probability and Statistics)
By Natalia Markovich
Publisher: Wiley-Interscience
Number Of Pages: 336
Publication Date: 2007-12-21
ISBN-10 / ASIN: 0470510870
ISBN-13 / EAN: 9780470510872
Book Description:
Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution.
The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function.
Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.

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(32) Nonparametric Analysis of Univariate Heavy-Tailed Data.pdf

大小:4.85 MB

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huntaway

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tanzhijun

2009-11-17 23:27:43

好书，不过有兴趣可以收集一下《handbooks of statistics》,相当全。

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