Nonlinear Time Series: Nonparametric and Parametric Methods / Edition 1

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Overview

This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

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Product Details

  • ISBN-13: 9780387261423
  • Publisher: Springer-Verlag New York, LLC
  • Publication date: 8/4/2005
  • Series: Springer Series in Statistics
  • Edition description: 1st ed. 2003. 2nd printing 2005
  • Edition number: 1
  • Pages: 572
  • Sales rank: 976,894
  • Product dimensions: 1.18 (w) x 6.14 (h) x 9.21 (d)

Table of Contents

Introduction.- Characteristics of Time Series.- ARMA Modeling and Forecasting.- Parametric Nonlinear Time Series Models.- Nonparametric Density Estimation.- Smoothing in Time Series.- Spectral Density Estimation and Its Applications.- Nonparametric Models.- Model Validation.- Nonlinear Prediction.

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