Efficient and Adaptive Estimation for Semiparametr ic Models (Johns Hopkins Series in the Mathematical Sciences) - Hardcover
Synopsis
Wherever statistics is applied, the need to combine interpretable structure with a minimum of assumptions about random fluctuations leads to the use of semiparametric models. In theories of economic choice, for instance, decision making is modeled in part by parametric relations suggested by economic theory and in part by individual fluctuations about which little is known or assumed. Another well-known example, the proportional hazards model of survival analysis, permits an arbitrary baseline hazard rate for a human lifetime but postulates that such variables as medical treatment, age and gender act on the baseline only through parametric scaling factors. This book unifies the theory of estimation in such examples. The authors show how the classical information bounds developed for parametric models extend naturally to nonparametric and semiparametric models. They then apply these techniques in as broad a range of models as possible, illustrating the ease with which heuristic calculations of "optimal behaviour" can be carried out.
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Review
"Provides a comprehensive introduction and summary of the current state of understanding of the vast extension of the theory of regular parametric estimation to the case in which the parameter space is divided into a finite-dimensional and an infinite-dimensional component... An essential source book for anyone wishing to do research in this exciting area." -- Mathematical Reviews
"Makes an important contribution to modern mathematical statistics. The authors have done a fine job making this difficult area accessible for a broader audience. They have achieved this by including an abundance and variety of illustrative and important examples... Required reading for anyone interested in semiparametric models." -- Anton Schick, Journal of the American Statistical Association
"A thorough and deep account of the current state of play and is an essential source book for anyone wishing to do research in this exciting area." -- Jack Cuzick, Mathematical Reviews
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Efficient and Adaptive Estimation for Semiparametric Models (Johns Hopkins Studies in the Mathematical Sciences)
Published by
The Johns Hopkins University Press September 1993, 1993
ISBN 10: 0801845416
ISBN 13: 9780801845413
Used
Hardcover
Seller: Magus Books Seattle, Seattle, WA, U.S.A.
Seller rating 4 out of 5 stars
Hardcover. Condition: VG. No Jacket. used hardcover copy, lacking a dust jacket. light shelfwear, corners perhaps slightly bumped. pages and binding are clean, straight, and tight. there are no marks to the text or other serious flaws save for the lack of the original jacket. Seller Inventory # 1503776