Overview
- Author is one of the most important figures in modern statistics as well as a great expositor
- Unique approach brings a unified treatment to a topic that is usually lost by some at a lower level of statistical proficiency
- Discusses a broad range of applications, written at an elementary level suitable for non-statisticians in applied fields
Part of the book series: Springer Texts in Statistics (STS)
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About this book
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. The book is written at an elementary level and 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:
Lehmann/Casella, Theory at Point Estimation, 2nd ed. Springer-Verlag New York, Inc., 1998, ISBN 0- 387-98502-6
Lehmann, Testing Statistical Hypotheses, 2nd ed. Springer-Verlag New York, Inc., 1997, ISBN 0-387-94919-4
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Keywords
Table of contents (7 chapters)
Reviews
From a review:
EUROPEAN MATHEMATICAL SOCIETY
"The book also contains rich collection of problems and a useful list of references, and can be warmly recommended as a complementary text to lectures on mathematical statistics, as well as a textbook for more advanced courses."
Editors and Affiliations
Bibliographic Information
Book Title: Elements of Large-Sample Theory
Editors: E. L. Lehmann
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/b98855
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1999
Hardcover ISBN: 978-0-387-98595-4Published: 04 December 1998
Softcover ISBN: 978-1-4419-3136-8Published: 19 November 2010
eBook ISBN: 978-0-387-22729-0Published: 18 April 2006
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XII, 632
Topics: Statistical Theory and Methods