Elements of Large-Sample Theory / Edition 1

Elements of Large-Sample Theory / Edition 1

by E.L. Lehmann
     
 

Elements of Large Sample Theory 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 written at an elementary level. The book is suitable for students at the Master's level in statistics and in aplied fields

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Overview

Elements of Large Sample Theory 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 written at an elementary level. The book is suitable for students at the Master's level in statistics and in aplied fields who have a background of two years of calculus.
E.L. Lehmann is Professor of Statistics Emeritus at the University of California, Berkeley. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands, and the University of Chicago.
Also available:
E.L. Lehmann and George Casella, Theory at Point Estimation, Second Edition. Springer-Verlag New York, Inc., 1998, 640 pp., Cloth, ISBN 0-387-98502-6.
E.L. Lehmann, Testing Statistical Hypotheses, Second Edition. Springer-Verlag New York, Inc., 1997, 624 pp., Cloth, ISBN 0-387-94919-4.

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Product Details

ISBN-13:
9780387985954
Publisher:
Springer New York
Publication date:
12/04/1998
Series:
Springer Texts in Statistics Series
Edition description:
1st ed. 1999. Corr. 3rd printing 2004
Pages:
632
Sales rank:
1,386,263
Product dimensions:
9.21(w) x 6.14(h) x 1.44(d)

Table of Contents

Mathematical Background
• Convergence in Probability and in Law
• Performance of Statistical Tests
• Estimation* Multivariate Extensions
• Nonparametric Estimation
• Efficient Estimators and Tests *

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