On Selecting Models for Nonlinear Time Series

On Selecting Models for Nonlinear Time Series (1995)

by Kevin Judd , Alistair Mees

Venue:	Physica D
Citations:	36 - 11 self

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Datum	Value	Source
TITLE	On Selecting Models for Nonlinear Time Series	user correction - Legacy Corrections
AUTHOR NAME	Kevin Judd	user correction - Legacy Corrections
AUTHOR NAME	Alistair Mees	user correction - Legacy Corrections
ABSTRACT	Constructing models from time series with nontrivial dynamics involves the problem of how to choose the best model from within a class of models, or to choose between competing classes. This paper discusses a method of building nonlinear models of possibly chaotic systems from data, while maintaining good robustness against noise. The models that are built are close to the simplest possible according to a description length criterion. The method will deliver a linear model if that has shorter description length than a nonlinear model. We show how our models can be used for prediction, smoothing and interpolation in the usual way. We also show how to apply the results to identification of chaos by detecting the presence of homoclinic orbits directly from time series. 1 The Model Selection Problem As our understanding of chaotic and other nonlinear phenomena has grown, it has become apparent that linear models are inadequate to model most dynamical processes. Nevertheless, linear models...	user correction - Legacy Corrections
YEAR	1995	INFERENCE
VENUE	Physica D	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	426--444	INFERENCE
VOLUME	82	INFERENCE
CITATIONS	26 found	ParsCit 1.0