Approximation Theorems of Mathematical Statistics
30%
off

Approximation Theorems of Mathematical Statistics

4.33 (3 ratings by Goodreads)
By (author) 

Free delivery worldwide

Available. Dispatched from the UK in 2 business days
When will my order arrive?

Description

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.
show more

Product details

  • Paperback | 400 pages
  • 152 x 227 x 23mm | 588g
  • New York, United States
  • English
  • 0471219274
  • 9780471219279
  • 645,389

Back cover copy

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:

The tools and foundations that are basic to asymptotic theory in statistics 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 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" Statistics obtained as solutions of equations ("M-estimates"), linear functions of order statistics ("L-statistics"), and rank statistics ("R-statistics") Use of influence curves Approaches toward asymptotic relative efficiency of statistical test procedures
show more

Table of contents

Preliminary Tools and Foundations. The Basic Sample Statistics. Transformations of Given Statistics. Asymptotic Theory in Parametric Inference. U--Statistics. Von Mises Differentiable Statistical Functions. M--Estimates. L--Estimates. R--Estimates. Asymptotic Relative Efficiency. Appendix. References. Author Index. Subject Index.
show more

Review quote

"...even today it still provides a really good introduction into asymptotic statistics..."(Zentralblatt Math, Vol. 1001, No.01, 2003)
show more

About Robert J. Serfling

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

Rating details

3 ratings
4.33 out of 5 stars
5 67% (2)
4 0% (0)
3 33% (1)
2 0% (0)
1 0% (0)
Book ratings by Goodreads
Goodreads is the world's largest site for readers with over 50 million reviews. We're featuring millions of their reader ratings on our book pages to help you find your new favourite book. Close X