Approximate Bayes Estimation of Parameters of the NEAR(2) Mode

by Subashan Perera .

Abstract: The published method for parameter estimation of the NEAR(2) model suffers from estimates frequently falling outside of the parameter space when the sample size is small and/or the true values of the parameters are close to the boundary of the parameter space. In order to alleviate this problem, while retaining the asymptotic consistency of the published estimators, an approximate Bayes correction is suggested. The approximate Bayes correction treats the asymptotic distribution of the estimators as an approximate likelihood for the data and employs a prior distribution supported in the parameter space. The results of a simulation study are also presented.

Key Words: exponential, autoregressive, time series, random coefficients, two-stage conditional least squares, out-of-range estimates

Subashan Perera,

Editor: Dean Foster ,

READING THE ARTICLE: You can read the article in portable document (.pdf) format (927908 bytes.)

NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.

This page has been accessed 2294 times since July 24, 2006.

Return to the InterStat Home Page.