ENGLISH

Nonparametric Statistics for Stochastic Processes: Estimation and Prediction

By D. Bosq (auth.)

Book information

Publisher
Springer-Verlag New York
Year
1998
ISBN
9780387947136, 0387947132
DOI
10.1007/978-1-4612-1718-3
LCC
QA278.8
Open Library ID
OL22211313M
Language
english
Format
DJVU
Filesize
1 MB (1244646 bytes)
Series
Lecture Notes in Statistics 110
Edition
2
Pages
232\90
Library
mexmat
Time added
2009-07-20 03:45:11
generalStatistics

Description

This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rates of convergence which appear in continuous time are presented in Chapters 4 and 5. This second edition is extensively revised and it contains two new chapters. Chapter 6 discusses the surprising local time density estimator. Chapter 7 gives a detailed account of implementation of nonparametric method and practical examples in economics, finance and physics. Comarison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting. The prerequisite is a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the Unviersity of Paris 6 (Pierre et Marie Curie). He is Editor-in-Chief of "Statistical Inference for Stochastic Processes" and an editor of "Journal of Nonparametric Statistics". He is an elected member of the International Statistical Institute. He has published about 90 papers or works in nonparametric statistics and four books.

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