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Activity Number: 250
Type: Invited
Date/Time: Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #303092
Title: Estimation Methods for Multivariate Linear Time Series
Author(s): Prabir Burman*+ and Metoyer N. Candace
Companies: University of California, Davis and Pacific Northwest National Laboratory
Address: Department of Statistics, Davis, CA, 95616,
Keywords: Time series ; Multivariate ; Nonparametric
Abstract:

Nonparametric factor analysis techniques are used to create a low-dimension co-integration model for a multivariate time series with stochastic trend. The method of penalized least-squares is employed in order to obtain a closed-form estimate of the trend. Asymptotic results for the mean square error of the estimator are provided and the proposed procedures are applied to real time series data.

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