Abstract #300600

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JSM 2002 Abstract #300600
Activity Number: 179
Type: Contributed
Date/Time: Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #300600
Title: On the Asymptotic Distribution of a Multivariate GR-Estimate for a VAR(p) Time Series
Author(s): Jeff Terpstra*+ and M. Rao
Affiliation(s): North Dakota State University and North Dakota State University
Address: P.O. Box 5575 Waldron 201H, Fargo, North Dakota, 58105, USA
Keywords: Asymptotic normality ; GR-Estimates ; MGR-Estimates ; Robust ; Vector autoregressive time series
Abstract:

This presentation discusses a new class of estimates for estimating the parameters of a vector-autoregressive time series. The estimates minimize a sum of weighted pairwise Euclidean distances and extend the univariate GR-estimates of Terpstra et al. (2001a; 2001b) to the multivariate model. Asymptotic linearity properties are derived for the so-called MGR-estimate. Based on these properties, the MGR-estimate is shown to be asymptotically normal at the square root of n rate. This result is valid for both symmetric and asymmetric error distributions. Some asymptotic relative efficiency comparisons between the MGR-estimate and the classical least-squares estimate will also be presented.

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