Efficient And Adaptive Estimation For Semiparametric Models

Download Efficient And Adaptive Estimation For Semiparametric Models full books in PDF, epub, and Kindle. Read online free Efficient And Adaptive Estimation For Semiparametric Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!


Related Books

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
Efficient and Adaptive Estimation for Semiparametric Models
Language: en
Pages: 560
Authors: Peter J. Bickel
Categories: Mathematics
Type: BOOK - Published: 1993 - Publisher:

DOWNLOAD EBOOK

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 situat
Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life
Language: en
Pages: 566
Authors: M.S. Nikulin
Categories: Mathematics
Type: BOOK - Published: 2013-11-11 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained vol
Semiparametric Regression
Language: en
Pages: 410
Authors: David Ruppert
Categories: Mathematics
Type: BOOK - Published: 2003-07-14 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that
Estimation in Semiparametric Models
Language: en
Pages: 116
Authors: Johann Pfanzagl
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Assume one has to estimate the mean J x P( dx) (or the median of P, or any other functional t;;(P)) on the basis ofi.i.d. observations from P. Ifnothing is know