JSM 2005 Online Program

Abstract #303877

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:	141
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	General Methodology
Abstract - #303877
Title:	Shapes of Stationary Autocovariances
Author(s):	Ying Zhao*+ and Robert Lund
Companies:	University of Georgia and Clemson University
Address:	104 College Station RD, Athens, GA, 30605, United States
Keywords:	Autocorrelation ; Convergence Rate ; Decreasing Hazard Rate ; Increasing Likelihood Ratio ; New Better than Used ; Partial Autocorrelation
Abstract:	This paper introduces stochastic shape orderings for the autocorrelation (ACF) and partial autocorrelation (PACF) functions of stationary time series and explores some of their convergence rate ramifications. The shapes explored include increasing likelihood ratio; decreasing hazard rate; and new, better-than-used structures familiar from stochastic processes settings. Given the utility of such orderings in stochastic processes, the theme is expected to prove fruitful. Examples of autoregressive moving-average time series having these shapes are first presented. The shapes are then applied to obtain explicit geometric convergence rates of some one-step-ahead forecasting quantities, particularly for mean squared prediction errors and Innovations Algorithm coefficients. It is expected such shape orderings eventually will be useful in likelihood computations, forecasting, and quantifying closeness of weighted and least-squares estimators.

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