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A Course in Large Sample Theory

A Course in Large Sample Theory PDF Author: Thomas S. Ferguson
Publisher: Routledge
ISBN: 1351470051
Category : Mathematics
Languages : en
Pages : 256

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Book Description
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.

A Course in Large Sample Theory

A Course in Large Sample Theory PDF Author: Thomas S. Ferguson
Publisher: Routledge
ISBN: 1351470051
Category : Mathematics
Languages : en
Pages : 256

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Book Description
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.

A Course in Mathematical Statistics and Large Sample Theory

A Course in Mathematical Statistics and Large Sample Theory PDF Author: Rabi Bhattacharya
Publisher: Springer
ISBN: 1493940325
Category : Mathematics
Languages : en
Pages : 389

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Book Description
This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

Elements of Large-Sample Theory

Elements of Large-Sample Theory PDF Author: E.L. Lehmann
Publisher: Springer Science & Business Media
ISBN: 0387227296
Category : Mathematics
Languages : en
Pages : 632

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Book Description
Written by one of the main figures in twentieth century statistics, this book provides a unified treatment of first-order large-sample theory. It discusses a broad range of applications including introductions to density estimation, the bootstrap, and the asymptotics of survey methodology. The book is written at an elementary level making it accessible to most readers.

Asymptotic Theory of Statistics and Probability

Asymptotic Theory of Statistics and Probability PDF Author: Anirban DasGupta
Publisher: Springer Science & Business Media
ISBN: 0387759700
Category : Mathematics
Languages : en
Pages : 722

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Book Description
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 in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.

Large Sample Techniques for Statistics

Large Sample Techniques for Statistics PDF Author: Jiming Jiang
Publisher: Springer Science & Business Media
ISBN: 144196827X
Category : Mathematics
Languages : en
Pages : 610

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Book Description
In a way, the world is made up of approximations, and surely there is no exception in the world of statistics. In fact, approximations, especially large sample approximations, are very important parts of both theoretical and - plied statistics.TheGaussiandistribution,alsoknownasthe normaldistri- tion,is merelyonesuchexample,dueto thewell-knowncentrallimittheorem. Large-sample techniques provide solutions to many practical problems; they simplify our solutions to di?cult, sometimes intractable problems; they j- tify our solutions; and they guide us to directions of improvements. On the other hand, just because large-sample approximations are used everywhere, and every day, it does not guarantee that they are used properly, and, when the techniques are misused, there may be serious consequences. 2 Example 1 (Asymptotic? distribution). Likelihood ratio test (LRT) is one of the fundamental techniques in statistics. It is well known that, in the 2 “standard” situation, the asymptotic null distribution of the LRT is?,with the degreesoffreedomequaltothe di?erencebetweenthedimensions,de?ned as the numbers of free parameters, of the two nested models being compared (e.g., Rice 1995, pp. 310). This might lead to a wrong impression that the 2 asymptotic (null) distribution of the LRT is always? . A similar mistake 2 might take place when dealing with Pearson’s? -test—the asymptotic distri- 2 2 bution of Pearson’s? -test is not always? (e.g., Moore 1978).

Large Sample Methods in Statistics

Large Sample Methods in Statistics PDF Author: Pranab K. Sen
Publisher: CRC Press
ISBN: 9780412042218
Category : Mathematics
Languages : en
Pages : 400

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Book Description
This text bridges the gap between sound theoretcial developments and practical, fruitful methodology by providing solid justification for standard symptotic statistical methods. It contains a unified survey of standard large sample theory and provides access to more complex statistical models that arise in diverse practical applications.

A Course in the Large Sample Theory of Statistical Inference

A Course in the Large Sample Theory of Statistical Inference PDF Author:
Publisher:
ISBN: 9781498726061
Category :
Languages : en
Pages :

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Book Description


A Course in Mathematical Statistics and Large Sample Theory

A Course in Mathematical Statistics and Large Sample Theory PDF Author: Rabi Bhattacharya
Publisher: Springer
ISBN: 9781493940301
Category : Mathematics
Languages : en
Pages : 389

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Book Description
This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

Confidence, Likelihood, Probability

Confidence, Likelihood, Probability PDF Author: Tore Schweder
Publisher: Cambridge University Press
ISBN: 0521861608
Category : Business & Economics
Languages : en
Pages : 544

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Book Description
This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.

Theory of Statistics

Theory of Statistics PDF Author: Mark J. Schervish
Publisher: Springer Science & Business Media
ISBN: 1461242509
Category : Mathematics
Languages : en
Pages : 716

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Book Description
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.