**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.

**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.

**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.

**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.

**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.

**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).

**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.

**Author**:

**Publisher:**
**ISBN:** 9781498726061

**Category : **
**Languages : **en

**Pages : **
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**Book Description**

**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.

**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.

**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.