Elements of Large-Sample Theory
Springer Science & Business Media, 1999 - Mathematics - 631 pages
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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Review: Elements of Large-Sample TheoryUser Review - Daniel Babiak - Goodreads
AMAZING Read full review
Review: Elements of Large-Sample TheoryUser Review - Joecolelife - Goodreads
Erich Lehmann is well known for his advanced statistical texts on hypothesis testing and estimation. he has also written a nice intermediate level text on nonparametric methods based on ranks. This ... Read full review