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Semiparametric Theory and Missing Data (Springer Series in Statistics) PDF

392 Pages·2006·2.281 MB·English
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by Anastasios A. Tsiatis| 2006| 392 pages| 2.281| English

About Semiparametric Theory and Missing Data (Springer Series in Statistics)

This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Detailed Information

Author:Anastasios A. Tsiatis
Publication Year:2006
ISBN:387324488
Pages:392
Language:English
File Size:2.281
Format:PDF
Price:FREE
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