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

Author:
Subashan Perera, sperera@kumc.edu

Editor: Dean Foster , foster@compstat.wharton.upenn.edu

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