JSM 2005 Online Program

Abstract #303069

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	492
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Section on Statistics and the Environment
Abstract - #303069
Title:	Mixture Periodic Autoregressive Time Series Models
Author(s):	Qin Shao*+
Companies:	The University of Toledo
Address:	2801 W Bancroft St, Toledo, OH, 43606, United States
Keywords:	Periodically Correlated Time ; Periodic Autocovariances ; Mixture Periodic Autoregressive models ; EM algorithm
Abstract:	Mixture periodic autoregressive models are introduced to fit periodic time series with asymmetric or multimodal distributions. The stationary conditions of such series are derived, the asymptotic property of maximum likelihood estimators is obtained, and the application of EM algorithm is discussed. The new model class is illustrated by analyzing the particulate matter concentrations in Cleveland, Ohio.

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