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eBook Efficient and Adaptive Estimation for Semiparametric Models (1384) download

by Chris A.J. Klaassen,Ya'acov Ritov,Jon A. Wellner,Peter J. Bickel

eBook Efficient and Adaptive Estimation for Semiparametric Models (1384) download ISBN: 0387984739
Author: Chris A.J. Klaassen,Ya'acov Ritov,Jon A. Wellner,Peter J. Bickel
Publisher: Springer; 1998 edition (May 8, 1998)
Language: English
Pages: 588
ePub: 1763 kb
Fb2: 1935 kb
Rating: 4.4
Other formats: doc docx lrf rtf
Category: Math Sciences
Subcategory: Mathematics

This book is about estimation in situations where we believe we have enough knowledge to model some features of the data . Bibliographic Information. Efficient and Adaptive Estimation for Semiparametric Models.

This book is about estimation in situations where we believe we have enough knowledge to model some features of the data parametrically, but are unwilling to assume anything for other features. Such models have arisen in a wide variety of contexts in recent years, particularly in economics, epidemiology, and astronomy. The complicated structure of these models typically requires us to consider nonlinear estimation procedures which often can only be implemented algorithmically.

Peter J. Bickel (Author), Chris . Klaassen (Author), Ya'acov Ritov (Author), Jon A. Wellner (Author) & 1 more.

Find all the books, read about the author, and more. Are you an author? Learn about Author Central. Peter J. ISBN-13: 978-0387984735.

Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them

Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. 1. When the Uncertainty Principle Goes to 11 - or, How to Explain Quantum Physics with Heavy Metal.

PDF On Jan 1, 1998, P. J. Bickel and others published Efficient and Adaptive Estimation for . All content in this area was uploaded by Chris . Bickel, C. A. Klaassen, Y. Ritov and J. Wellner.

All content in this area was uploaded by Chris . Klaassen on Jul 08, 2019.

Items related to Efficient and Adaptive Estimation for Semiparametric. Dr. Bickel; Dr. Chris A. Klaassen; Dr. Ya'acov Ritov; Professor Jon A. Wellner; Chris . Klaassen; Ya'Acov Ritov; Jon Wellner Efficient and Adaptive Estimation for Semiparametric Models (Johns Hopkins Studies in the Mathematical Sciences). ISBN 13: 9780801845413. Originating with the 1983 Mathematical Sciences Lectures at Johns Hopkins given by Peter J. Bickel and Jon A. Wellner, this volume is about estimation in situations where enough is known to model some features of the data parametrically but not enough is known to assume anything for other features.

Efficient and adaptive estimation for semiparametric models Adaptive estimation in time-series models. FC Drost, CAJ Klaassen, BJM Werker

Efficient and adaptive estimation for semiparametric models. PJ Bickel, CAJ Klaassen, PJ Bickel, Y Ritov, J Klaassen, JA Wellner,. Johns Hopkins University Press, 1993. Efficient and adaptive inference in semiparametric models. PJ Bickel, CAJ Klaassen, Y Ritov, JA Wellner. Johns Hopkins University Press, Baltimore, 1993. Adaptive estimation in time-series models. FC Drost, CAJ Klaassen, BJM Werker. The Annals of Statistics 25 (2), 786-817, 1997. Efficient estimation in the bivariate normal copula model: normal margins are least favourable.

Efficient and adaptive estimation for semiparametric models 1996. Efficient estimation in the errors in variables model. The Annals of Statistics 15 (2), 513-540, 1987.

Efficient and adaptive estimation for semiparametric models. Simultaneous analysis of Lasso and Dantzig selector. PJ Bickel, Y Ritov, AB Tsybakov. The Annals of Statistics 37 (4), 1705-1732, 2009.

Bickel, Peter . Chris . Klaassen; Ya’acov Ritov; Jon A. Wellner (1998). ISBN 978-0-387-98473-5. Other useful references. php?title Adaptive estimator&oldid 887537817".

This book is about estimation in situations where we believe we have enough knowledge to model some features of the data parametrically, but are unwilling to. .Klaassen, Jon A. Wellner, Peter J. Bickel. Place of Publication. The theory of these procedures is necessarily based on asymptotic approximations.

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 data set. Such models have arisen in a wide context in recent years, and involve new nonlinear estimation procedures. Statistical models of this type are directly applicable to fields such as economics, epidemiology, and astronomy.