Approximation Theorems of Mathematical Statistics
Robert J. Serfling
set 2009 · John Wiley & Sons
Ebook
400
pagine
reportValutazioni e recensioni non sono verificate Scopri di più
Informazioni su questo ebook
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
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
Informazioni sull'autore
ROBERT J. SERFLING, PhD, is a Professor at the Department of Mathematical Sciences at the University of Texas at Dallas.
Valuta questo ebook
Dicci cosa ne pensi.
Informazioni sulla lettura
Smartphone e tablet
Installa l'app Google Play Libri per Android e iPad/iPhone. L'app verrà sincronizzata automaticamente con il tuo account e potrai leggere libri online oppure offline ovunque tu sia.
Laptop e computer
Puoi ascoltare gli audiolibri acquistati su Google Play usando il browser web del tuo computer.
eReader e altri dispositivi
Per leggere su dispositivi e-ink come Kobo e eReader, dovrai scaricare un file e trasferirlo sul dispositivo. Segui le istruzioni dettagliate del Centro assistenza per trasferire i file sugli eReader supportati.
