Abstract #302209

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JSM 2003 Abstract #302209
Activity Number: 158
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: ASA-SRCOS So. Regional Cmte on Stats Summer Research
Abstract - #302209
Title: Functional Coefficient Autoregressive Modeling for Multivariate Temporal Data
Author(s): Jane Lea Harvill*+ and Bonnie K. Ray
Companies: Mississippi State University and IBM T. J. Watson Research Center
Address: PO Box MA, Mississippi State, MS, 39762-5921,
Keywords: nonlinear vector time series ; functional coefficient model ; bootstrap test for nonlinearity
Abstract:

Univariate nonlinear time series models have been used extensively over the past 15 to 20 years to model complex dynamic systems that cannot be adequately represented using linear models. A very general type of nonlinear time series model is the univariate functional coefficient autoregressive (FCAR) model, where the autoregressive coefficients are allowed to change as a function of one or more variables, which may be lagged values of the series or exogeneous predictors, including, for example, time. We extend the univariate FCAR model to the vector time series framework. A bootstrap test for vector time series nonlinearity is presented, and is shown to out-perform existing tests for a number of different multivariate nonlinear models. FCAR methods are applied to a number of different environmental datasets to illustrate utility. Extensions to spatial-temporal modeling will also be mentioned.

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