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Download the fantastic book titled Inference and Asymptotics written by D.R. Cox, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Inference and Asymptotics", which was released on 19 October 2017. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.

Summary of Inference and Asymptotics by D.R. Cox PDF

Our book Asymptotic Techniquesfor Use in Statistics was originally planned as an account of asymptotic statistical theory, but by the time we had completed the mathematical preliminaries it seemed best to publish these separately. The present book, although largely self-contained, takes up the original theme and gives a systematic account of some recent developments in asymptotic parametric inference from a likelihood-based perspective. Chapters 1-4 are relatively elementary and provide first a review of key concepts such as likelihood, sufficiency, conditionality, ancillarity, exponential families and transformation models. Then first-order asymptotic theory is set out, followed by a discussion of the need for higher-order theory. This is then developed in some generality in Chapters 5-8. A final chapter deals briefly with some more specialized issues. The discussion emphasizes concepts and techniques rather than precise mathematical verifications with full attention to regularity conditions and, especially in the less technical chapters, draws quite heavily on illustrative examples. Each chapter ends with outline further results and exercises and with bibliographic notes. Many parts of the field discussed in this book are undergoing rapid further development, and in those parts the book therefore in some respects has more the flavour of a progress report than an exposition of a largely completed theory.


Detail About Inference and Asymptotics PDF

  • Author : D.R. Cox
  • Publisher : Routledge
  • Genre : Mathematics
  • Total Pages : 360 pages
  • ISBN : 1351438565
  • PDF File Size : 10,6 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Inference and Asymptotics

Inference and Asymptotics
  • Publisher : Routledge
  • File Size : 39,5 Mb
  • Release Date : 19 October 2017
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Our book Asymptotic Techniquesfor Use in Statistics was originally planned as an account of asymptotic statistical theory, but by the time we had completed the mathematical preliminaries it seemed best

Inference and Asymptotics

Inference and Asymptotics
  • Publisher : CRC Press
  • File Size : 41,6 Mb
  • Release Date : 01 March 1994
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Likelihood and its many associated concepts are of central importance in statistical theory and applications. The theory of likelihood and of likelihood-like objects (pseudo-likelihoods) has undergone extensive and important developments

Asymptotic Theory of Statistical Inference

Asymptotic Theory of Statistical Inference
  • Publisher : Unknown Publisher
  • File Size : 34,6 Mb
  • Release Date : 16 January 1987
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Probability and stochastic processes; Limit theorems for some statistics; Asymptotic theory of estimation; Linear parametric inference; Martingale approach to inference; Inference in nonlinear regression; Von mises functionals; Empirical characteristic function

Inference, Asymptotics, and Applications

Inference, Asymptotics, and Applications
  • Publisher : World Scientific
  • File Size : 37,6 Mb
  • Release Date : 10 March 2017
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This book showcases the innovative research of Professor Skovgaard, by providing in one place a selection of his most important and influential papers. Introductions by colleagues set in context the

Asymptotic Optimal Inference for Non-ergodic Models

Asymptotic Optimal Inference for Non-ergodic Models
  • Publisher : Springer Science & Business Media
  • File Size : 55,7 Mb
  • Release Date : 06 December 2012
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This monograph contains a comprehensive account of the recent work of the authors and other workers on large sample optimal inference for non-ergodic models. The non-ergodic family of models can

Robust Statistical Procedures

Robust Statistical Procedures
  • Publisher : John Wiley & Sons
  • File Size : 49,8 Mb
  • Release Date : 19 April 1996
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A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the

Asymptotics in Statistics

Asymptotics in Statistics
  • Publisher : Springer Science & Business Media
  • File Size : 42,7 Mb
  • Release Date : 06 December 2012
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This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in

Asymptotic Theory of Statistics and Probability

Asymptotic Theory of Statistics and Probability
  • Publisher : Springer Science & Business Media
  • File Size : 27,8 Mb
  • Release Date : 07 March 2008
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This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique

Principles of Statistical Inference

Principles of Statistical Inference
  • Publisher : World Scientific
  • File Size : 42,7 Mb
  • Release Date : 05 August 1997
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In this book, an integrated introduction to statistical inference is provided from a frequentist likelihood-based viewpoint. Classical results are presented together with recent developments, largely built upon ideas due to