Semiparametric Theory and Missing Data

Semiparametric Theory and Missing Data
Author :
Publisher : Springer Science & Business Media
Total Pages : 392
Release :
ISBN-10 : 9780387373454
ISBN-13 : 0387373454
Rating : 4/5 (454 Downloads)

Book Synopsis Semiparametric Theory and Missing Data by : Anastasios Tsiatis

Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Semiparametric Theory and Missing Data Related Books

Semiparametric Theory and Missing Data
Language: en
Pages: 392
Authors: Anastasios Tsiatis
Categories: Mathematics
Type: BOOK - Published: 2007-01-15 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner.
Efficient and Adaptive Estimation for Semiparametric Models
Language: en
Pages: 588
Authors: Peter J. Bickel
Categories: Mathematics
Type: BOOK - Published: 1998-06-01 - Publisher: Springer

DOWNLOAD EBOOK

This book deals with estimation in situations in which there is believed to be enough information to model parametrically some, but not all of the features of a
Bayesian Nonparametrics
Language: en
Pages: 311
Authors: J.K. Ghosh
Categories: Mathematics
Type: BOOK - Published: 2006-05-11 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The b
Gaussian and Non-Gaussian Linear Time Series and Random Fields
Language: en
Pages: 272
Authors: Murray Rosenblatt
Categories: Mathematics
Type: BOOK - Published: 2000 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discuss
Asymptotic Theory of Statistical Inference for Time Series
Language: en
Pages: 0
Authors: Masanobu Taniguchi
Categories: Mathematics
Type: BOOK - Published: 2012-10-23 - Publisher: Springer

DOWNLOAD EBOOK

The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not re