Dimension estimation and models

Dimension estimation and models

by Tong, Howell

Type Book
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This volume is the first in the new series Nonlinear Time Series and Chaos. The general aim of the series is to provide a bridge between the two communities by inviting prominent researchers in their respective fields to give a systematic account of their chosen topics, starting at the beginning and ending with the latest state. It is hoped that researchers in both communities will find the topics relevant and thought provoking. In this volume, the first chapter, written by Professor Colleen Cu…

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Title Statements

  • Full title :Dimension estimation and models / editor, Howell Tong.

Summary

This volume is the first in the new series Nonlinear Time Series and Chaos. The general aim of the series is to provide a bridge between the two communities by inviting prominent researchers in their respective fields to give a systematic account of their chosen topics, starting at the beginning and ending with the latest state. It is hoped that researchers in both communities will find the topics relevant and thought provoking. In this volume, the first chapter, written by Professor Colleen Cutler, is a comprehensive account of the theory and estimation of fractal dimension, a topic of central importance in dynamical systems, which has recently attracted the attention of the statisticians. As it is natural to study a stochastic dynamical system within the framework of Markov chains, it is therefore relevant to study their limiting behaviour. The second chapter, written by Professor Kung-Sik Chan, reviews some limit theorems of Markov chains and illustrates their relevance to chaos. The next three chapters are concerned with specific models. Briefly, chapter three by Professor Peter Lewis and Dr Bonnie Ray and chapter four by Professor Peter Brockwell generalise the class of self-exciting threshold autoregressive models in different directions. In chapter three, the new and powerful methodology of multivariate adaptive regression splines (MARS) is adapted to time series data. Its versatility is illustrated by reference to the very interesting and complex sea surface temperature data. Chapter four exploits the greater tractability of continuous-time Markov approach to discrete-time data. The approach is particularly relevant to irregularly sampled data. The concluding chapter, by Professor Pham Dinh Tuan, is likely to be the most definitive account of bilinear models in discrete time to date.

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Edition Statements

  • Publication Date:©1993.

Publication Statements

  • Publisher(s):World Scientific
  • Place of Publication:Singapore
  • Language:eng
  • Publication Date:©1993.

The Physical Object

  • Description:1 online resource (vii, 223 pages) : : illustrations.

Edition Identifiers

  • ISBN:9789810213534, 9810213530, 9789814317382, 9814317381
  • oclc:ocn842259736
  • LC Classification:QA280
  • Dewey Decimal:519.5/5

Table of Contents

A Review of the Theory and Estimation of Fractal Dimension / Colleen D. Cutler -- A Review of Some Limit Theorems of Markov Chains and Their Applications / K.S. Chan -- Nonlinear Modeling of Multivariate and Categorical Time Series Using Multivariate Adaptive Regression Splines / Peter A.W. Lewis and Bonnie K. Ray -- Threshold ARMA Processes in Continuous Time / Peter J. Brockwell -- Bilinear Time Series Models / Pham Dinh Tuan.

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