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Maximum Penalized Likelihood Estimation Vol 2- Regression.pdf

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文档介绍

文档介绍:Springer Series in Statistics
Advisors:
P. Bickel, P. Diggle, S. Fienberg, U. Gather,
I. Olkin, S. Zeger
For further volumes:
ies/692
. Eggermont · . ia
Maximum Penalized
Likelihood Estimation
Volume II: Regression
123
. Eggermont
Department of Food and Resource Economics
University of Delaware
Newark, DE 19716
USA
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Department of Food and Resource Economics
University of Delaware
Newark, DE 19716
USA
******@
ISBN 978-0-387-40267-3 e-ISBN 978-0-387-68902-9
DOI
Springer Dordrecht Heidelberg London New York
Library of Congress Control Number: 2001020450
c Springer Science+Business Media, LLC 2009
All rights reserved. This work may not be translated or copied in whole or in part without the written
permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York,
NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in
connection with any form of information storage and retrieval, electronic adaptation, computer
software, or by similar or dissimilar methodology now known or hereafter developed is forbidden.
The use in this publication of trade names, trademarks, service marks, and similar terms, even if
they are not identified as such, is not to be taken as an expression of opinion as to whether or not
they are subject to proprietary rights.
Printed on acid-free paper
Springer is part of Springer Science+Business Media ()
To Jeanne and Tyler
To Cindy
Preface
This is the second volume of a text on the theory and practice of maximum
penalized likelihood estimation. It is intended for graduate students in sta-
tistics, operations research, and applied mathematics, as well as researchers
and practitioners in the field. The present volume was supposed to have a
short chapter on nonparametric regression but was intended to deal mainly
with inverse problems. However, the chapter on nonparametric r