Approximation Theorems of Mathematical Statistics

This convenient paperback edition makes a seminal text instatistics accessible to a new generation of students andpractitioners. Approximation Theorems of Mathematical Statisticscovers a broad range of limit theorems useful in mathematicalstatistics, along with methods of proof and techniques ofapplication. The manipulation of "probability" theorems to obtain"statistical" theorems is emphasized. Besides a knowledge of thesebasic statistical theorems, this lucid introduction to the subjectimparts an appreciation of the instrumental role of probabilitytheory.

The book makes accessible to students and practicing professionalsin statistics, general mathematics, operations research, andengineering the essentials of:

* The tools and foundations that are basic to asymptotic theory instatistics

* The asymptotics of statistics computed from a sample, includingtransformations of vectors of more basic statistics, with emphasison asymptotic distribution theory and strong convergence

* Important special classes of statistics, such as maximumlikelihood estimates and other asymptotic efficient procedures; W.Hoeffding's U-statistics and R. von Mises's "differentiablestatistical functions"

* Statistics obtained as solutions of equations ("M-estimates"),linear functions of order statistics ("L-statistics"), and rankstatistics ("R-statistics")

* Use of influence curves

* Approaches toward asymptotic relative efficiency of statisticaltest procedures

*"synopsis" may belong to another edition of this title.*

Covers a broad range of limit theorems for mathematical statistics, including proof methods and application techniques. Emphasizes manipulation of probability theorems to obtain statistical theorems. Imparts a knowledge of these basic statistical theorems, as well as an appreciation of the instrumental role of probability theory and a perspective on practical needs for its further development. Assumes introductory graduate knowledge of probability theory and mathematical statistics.

**ROBERT J. SERFLING**, PhD, is a Professor at the Department of Mathematical Sciences at the University of Texas at Dallas.

*"About this title" may belong to another edition of this title.*

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ISBN 13: 9780471219279

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**Book Description **John Wiley and Sons Ltd, United States, 2002. Paperback. Condition: New. Language: English. Brand new Book. This paperback reprint of one of the best in the field covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of "probability" theorems to obtain "statistical" theorems is emphasized. Seller Inventory # AAH9780471219279

Published by
John Wiley and Sons Ltd, United States
(2001)

ISBN 10: 0471219274
ISBN 13: 9780471219279

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**Book Description **John Wiley and Sons Ltd, United States, 2001. Paperback. Condition: New. Language: English . Brand New Book. Approximation Theorems of Mathematical Statistics This convenient paperback edition makes a seminal text in statistics accessible to a new generation of students and practitioners. Approximation Theorems of Mathematical Statistics covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of probability theorems to obtain statistical theorems is emphasized. Besides a knowledge of these basic statistical theorems, this lucid introduction to the subject imparts an appreciation of the instrumental role of probability theory. The book makes accessible to students and practicing professionals in statistics, general mathematics, operations research, and engineering the essentials of: â The tools and foundations that are basic to asymptotic theory in statistics â The asymptotics of statistics computed from a sample, including transformations of vectors of more basic statistics, with emphasis on asymptotic distribution theory and strong convergence â Important special classes of statistics, such as maximum likelihood estimates and other asymptotic efficient procedures; W. Hoeffding s U-statistics and R. von Mises s differentiable statistical functions â Statistics obtained as solutions of equations ( M-estimates ), linear functions of order statistics ( L-statistics ), and rank statistics ( R-statistics ) â Use of influence curves â Approaches toward asymptotic relative efficiency of statistical test procedures. Seller Inventory # AAH9780471219279

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