Nonparametric statistics for stochastic processes

estimation and prediction

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Last edited by Open Library Bot
April 14, 2010 | History

Nonparametric statistics for stochastic processes

estimation and prediction

This book is devoted to the theory and applications of nonparametric functional estimation and prediction. The second edition is extensively revised and contains two new chapters. One discusses the surprising local time density estimator. The other gives a detailed account of the implementation of nonparametric methods and practical examples in economics, finance, and physics. A comparison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting.

The book assumes a knowledge of classical probability theory and statistics.

Publish Date
Publisher
Springer
Language
English
Pages
169

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Book Details


Edition Notes

Includes bibliographical references (p. 156-165) and index.

Published in
New York
Series
Lecture notes in statistics ;, 110, Lecture notes in statistics (Springer-Verlag) ;, v. 110.

Classifications

Dewey Decimal Class
519.5/4
Library of Congress
QA278.8 .B67 1996

The Physical Object

Pagination
xii, 169 p. :
Number of pages
169

Edition Identifiers

Open Library
OL976470M
ISBN 10
0387947132
LCCN
96013588

Work Identifiers

Work ID
OL1919489W

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
April 14, 2010 Edited by Open Library Bot Linked existing covers to the edition.
December 11, 2009 Edited by WorkBot link works
April 1, 2008 Created by an anonymous user Imported from Scriblio MARC record