Pitman's Measure of Closeness (PMC) is simply an idea whose time has come. Certainly there are many different ways to estimate unknown parameters, but which method should you use? Posed as an alternative to the concept of mean-squared-error, PMC is based on the probabilities of the closeness of competing estimators to an unknown parameter. Renewed interest in PMC over the last 20 years has motivated the authors to produce this book, which explores this method of comparison and its usefulness. Written with research oriented ...
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Pitman's Measure of Closeness (PMC) is simply an idea whose time has come. Certainly there are many different ways to estimate unknown parameters, but which method should you use? Posed as an alternative to the concept of mean-squared-error, PMC is based on the probabilities of the closeness of competing estimators to an unknown parameter. Renewed interest in PMC over the last 20 years has motivated the authors to produce this book, which explores this method of comparison and its usefulness. Written with research oriented statisticians and mathematicians in mind, but also considering the needs of graduate students in statistics courses, this book provides a thorough introduction to the methods and known results associated with PMC. Following a foreword by C .R. Rao, the first three chapters focus on basic concepts, history, controversy, paradoxes and examples associated with the PMC criterion.
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Publisher:
Society for Industrial and Applied Mathematics (SIAM)
Published:
1987
Language:
English
Alibris ID:
18071415747
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Seller's Description:
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Publisher:
Society for Industrial and Applied Mathematics (SIAM)
Published:
1987
Language:
English
Alibris ID:
18020118218
Shipping Options:
Standard Shipping: $4.79
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
Very Good. Lightly used, may have light reading wear and/or publisher's or previous owner's markings, but NO markings in text. Pasadena's finest new and used bookstore since 1992.