Download or read book Small Sample Asymptotics written by Christopher A. Field and published by IMS. This book was released on 1990 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Small Sample Asymptotics written by Elvezio M. Ronchetti and published by . This book was released on 1990 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied Asymptotics written by and published by . This book was released on 2007 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.

Download or read book Small Sample Asymptotics written by Christopher A. Field and published by . This book was released on 2008* with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This e-book is the product of Project Euclid and its mission to advance scholarly communication in the field of theoretical and applied mathematics and statistics. Project Euclid was developed and deployed by the Cornell University Library and is jointly managed by Cornell and the Duke University Press.

Download or read book Applied Asymptotics written by A. R. Brazzale and published by Cambridge University Press. This book was released on 2007-05-31 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods.

Download or read book Small Sample Asymptotics written by Field and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Overview of Small Sample Asymptotics written by Christopher A. Field and published by . This book was released on 1991 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Theoretic Approximation of Small Sample Distributions written by Ximing Wu and published by . This book was released on 2006 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a simple approach for approximating small sample distributions based on the method of minimum relative entropy density. Unlike previous studies that use this method as a curve-fitting tool, we focus on the 'small sample asymptotics' of the approximation to distributions of general statistics. We show that this method obtains not only the same asymptotic order of accuracy as that of the classical Edgeworth expansion and the exponential Edgeworth expansion by Field and Hampel (1982), but also the minimum Kullback-Leibler distance among all approximations of the same exponential family. The formulation of the minimum relative entropy density facilitates incorporating prior information through a reference density. Moreover, the introduction of a reference density frees us from the assumption of a bounded support, which is typically used in the existing literature. We discuss the selection of a proper reference density that ensures the integrability of the approximation on the real line under various moment constraints. Our numerical experiments show that the proposed method compares competitively with and often outperforms the Edgeworth and exponential Edgeworth expansions, especially when the sample size is small.

Download or read book Small Sample Asymptotics written by G. Diana and published by . This book was released on 1990 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Small Sample Asymptotics and Related Problems written by and published by . This book was released on 1990 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Expansions and Asymptotics for Statistics written by Christopher G. Small and published by CRC Press. This book was released on 2010-05-07 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asymptotic methods provide important tools for approximating and analysing functions that arise in probability and statistics. Moreover, the conclusions of asymptotic analysis often supplement the conclusions obtained by numerical methods. Providing a broad toolkit of analytical methods, Expansions and Asymptotics for Statistics shows how asymptoti

Download or read book Asymptotic Expansions of the Distributions of the Test Statistics for Overidentifying Restrictions in a System of Simultaneous Equations written by Stanford University. Institute for Mathematical Studies in the Social Sciences and published by . This book was released on 1979 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Small Sample Asymptotics Distributions of M estimators of Location written by Christopher A. Field and published by . This book was released on 1978 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Course in Large Sample Theory written by Thomas S. Ferguson and published by Routledge. This book was released on 2017-09-06 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Course in Large Sample Theory is presented in four parts. The first treats basic probabilistic notions, the second features the basic statistical tools for expanding the theory, the third contains special topics as applications of the general theory, and the fourth covers more standard statistical topics. Nearly all topics are covered in their multivariate setting.The book is intended as a first year graduate course in large sample theory for statisticians. It has been used by graduate students in statistics, biostatistics, mathematics, and related fields. Throughout the book there are many examples and exercises with solutions. It is an ideal text for self study.

Download or read book Applied Asymptotics written by A. R. Brazzale and published by Cambridge University Press. This book was released on 2007-05-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.

Download or read book Small Sample Asymptotics written by G. Diana and published by . This book was released on 1990 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymptotic Statistics written by A. W. van der Vaart and published by Cambridge University Press. This book was released on 2000-06-19 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master s level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.