Semiparametric Theory and Missing Data
Anastasios TsiatisThis 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.
Categories:
Year:
2006
Edition:
1
Publisher:
Springer
Language:
english
Pages:
391
ISBN 10:
0387324488
ISBN 13:
9780387324487
Series:
Springer Series in Statistics
File:
PDF, 2.55 MB
IPFS:
,
english, 2006