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Theory of Point Estimation (Springer Texts in Statistics) 2nd Edition

by Erich L. Lehmann (Author), George Casella (Author)
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Theory of Point Estimation: Second Edition (Springer Texts in Statistics)
Theory of Point Estimation: Second Edition (Springer Texts in Statistics)
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Since the publication in 1983 of Theory of Point Estimation, much new work has made it desirable to bring out a second edition. The inclusion of the new material has increased the length of the book from 500 to 600 pages; of the approximately 1000 references about 25% have appeared since 1983. The greatest change has been the addition to the sparse treatment of Bayesian inference in the first edition. This includes the addition of new sections on Equivariant, Hierarchical, and Empirical Bayes, and on their comparisons. Other major additions deal with new developments concerning the information in equality and simultaneous and shrinkage estimation. The Notes at the end of each chapter now provide not only bibliographic and historical material but also introductions to recent development in point estimation and other related topics which, for space reasons, it was not possible to include in the main text. The problem sections also have been greatly expanded. On the other hand, to save space most of the discussion in the first edition on robust estimation (in particu lar L, M, and R estimators) has been deleted. This topic is the subject of two excellent books by Hampel et al (1986) and Staudte and Sheather (1990). Other than subject matter changes, there have been some minor modifications in the presentation.
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  1. ISBN-10
    0387985026
  2. ISBN-13
    978-0387985022
  3. Edition
    2nd
  4. Publisher
    Springer
  5. Publication date
    August 13, 1998
  6. Part of series
    Springer Texts in Statistics
  7. Language
    English
  8. Dimensions
    6.38 x 1.28 x 9.53 inches
  9. Print length
    616 pages
  10. See all details
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Customer reviews

4.3 out of 5 stars
23 global ratings

Top reviews from the United States

fashionista
5.0 out of 5 stars Still covering, just skimmed
Reviewed in the United States on July 20, 2022
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Similar to Testing Statistical Hypotheses, most rigorous, great references
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Gary Bowers
5.0 out of 5 stars Clear and Concise
Reviewed in the United States on October 21, 2016
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The Theory of Point Estimation, 2nd Edition, by Lehmann and Casella belongs in every Statistician's library. The proofs are particularly well written in a highly accessible manner. If one wants to make clear and concise citations, this book is a must have for your thesis work.
3 people found this helpful
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Niro R
5.0 out of 5 stars Five Stars
Reviewed in the United States on January 18, 2017
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Great book for graduate students in Statistics, Biostatistics, and probability.
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Jia Li
4.0 out of 5 stars Good book
Reviewed in the United States on October 3, 2005
Good book, but a little abstract for me. It requires some knowledge of measure theory. Some definitions and theories are stated in a more "mathematical" language. "Statistical Inference" by George Casella would be a good reference for it.
3 people found this helpful
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Iris Ivy Gauran
5.0 out of 5 stars Five Stars
Reviewed in the United States on February 24, 2015
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It was more than what I expected.
One person found this helpful
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Pranav
2.0 out of 5 stars Most painful math textbook I ever had to use
Reviewed in the United States on January 30, 2022
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The primary issue with this book is that the author is trying to disseminate the knowledge in an almost prose-like form. In my opinion, this is a horrible way to teach theoretical statistics as it leaves the reader hunting and underlining left and right. In some cases, he accidentally leaves out parts of definitions. For example, when defining the sigma algebra in chapter 1; he doesn't mention that the sigma algebra must contain the empty set. While these little details might seem irrelevant in the big picture; it forces the reader to look to outside sources for definitions and doesn't serve as a compact reference.
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alacarte
3.0 out of 5 stars A good reference but sloppy and inconsistent
Reviewed in the United States on January 1, 2011
I used Theory of Point Estimation (hereafter, TPE) in a graduate course on statistical theory. I originally wrote a very negative review, but I have warmed up to the book over the past few months. Despite its flaws, it still remains a good resource with its many theorems and references, and it is infinitely more readable than its counterpart, Testing Statistical Hypotheses. However, I still would not recommend the book as a textbook for students trying to learn the material for the first time when there are many better options out there.

First, TPE seems to never have been proofread. Many of the exercises are wrong as stated, some incorrigibly so. Even if one is not interested in the exercises, many of the theorem statements and formulas in the exposition are wrong as well -- some so wrong that figuring out how they managed to so egregiously mistype the formula is an entertaining exercise in itself. For example, consider the absolutely nonsensical expression for the MRE estimator of a scale parameter under absolute error loss (Chapter 3, page 169, equation 3.16). And as with 99% of the errors in the book, this egregious error does not appear in the (very incomplete) errata on Casella's website, although apparently there is another error on the very same page.

Secondly, TPE is just not very clear. It seems that the authors could not make up their mind about how much mathematical background to assume, and the book makes the occasional nod to measure theory while glossing over the details. As a result, TPE does too little measure theory to appease the mathematically prepared reader, while doing too much for the book to be useful to a reader who lacks that background. Furthermore, an absurd number of proofs are omitted in the text, including proofs that are not that technical and would add a lot of intuition (for example, in Chapter 1, the result that a full-rank exponential family has a complete sufficient statistic).

I cannot recommend this book because of the innumerable errors and the spotty exposition. For the mathematically sophisticated reader, I recommend Jun Shao's excellent book Mathematical Statistics, which is more technical than TPE, but (paradoxically) clearer, more precise, and more accurate. Readers who would like a taste of statistical theory but lack the background in measure theory, should consider Casella's other book with Roger Berger, Statistical Inference.
14 people found this helpful
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Michael R. Chernick
5.0 out of 5 stars highly theoretical text
Reviewed in the United States on February 13, 2008
Erich Lehmann wrote this classic text on point estimation as the companion to his earlier masterpiece on hypothesis testing. The book lived up to the standard set by the other text. This edition, now published by Springer-Verlag was revised with the help of George Casella who is also an excellent writer. Another great reference book that statisticians should have on their bookshelf.
23 people found this helpful
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Top reviews from other countries

Rahul Roy
3.0 out of 5 stars Not delivered what was promised
Reviewed in India on September 10, 2023
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The book I received is not hard cover at all (although it says hardcover). Don't get me wrong.. the quality of the pages are good. But being a paperback version it is very hard to navigate through pages. A hardcover version would have been better.
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Rahul Roy
3.0 out of 5 stars Not delivered what was promised
Reviewed in India on September 10, 2023
The book I received is not hard cover at all (although it says hardcover). Don't get me wrong.. the quality of the pages are good. But being a paperback version it is very hard to navigate through pages. A hardcover version would have been better.
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One person found this helpful
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Admo
5.0 out of 5 stars Arrived in time and has a good quality
Reviewed in Canada on February 21, 2020
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The order arrived in time, and has a good quality. Totally satisfied!
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