|
Approximation Theorems of Mathematical Statistics | 
 enlarge | Author: Robert J. Serfling
Publisher: Wiley-Interscience
Category: Book
List Price: $118.95
Buy New: $82.89
You Save: $36.06 (30%)
New (20) Used (10) from $77.00
Rating:  1 reviews
Sales Rank: 124269
Media: Paperback
Pages: 400
Number Of Items: 1
Shipping Weight (lbs): 1.4
Dimensions (in): 9 x 6.1 x 1
ISBN: 0471219274
Dewey Decimal Number: 519
EAN: 9780471219279
Publication Date: December 21, 2001
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: Brand New, Perfect Condition, Please allow 4-14 business days for delivery. 100% Money Back Guarantee, Over 1,000,000 customers served.
| |
| Similar Items:
|
| Editorial Reviews:
Product Description
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
|
| Customer Reviews:
Great Reference April 19, 2001
Carlos Morales (Cambridge, MA USA)
8 out of 8 found this review helpful
As a graduate student in statistics, I have had plenty of opportunities to browse through the pages of this book in search of that theorem, technique, or tool that would be applicable to my own work. In many occasions I was succesful in such search. This title compiles and synthesizes a wealth of definitions, theorems, and techniques classically used in asymptotic theory of estimators. It is as much as possible a self-contained work with enough introductory material to be used independently of other references. A bit outdated now, and with minimal material on dependent random variables, this title is still a classic compendium on statistical approximation theory.
|
|
|
| |
