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Improved likelihood-based inference for the MA(1) model
Authors:Fang Chang  Marie Rekkas  Augustine Wong
Affiliation:1. Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3;2. Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, Canada V5A 1S6
Abstract:
An improved likelihood-based method is proposed to test for the significance of the first-order moving average model. Compared with commonly used tests which depend on the asymptotic properties of the maximum likelihood estimate and the likelihood ratio statistic, the proposed method has remarkable accuracy. Application of the method to a data set on book sales is presented to demonstrate the implementation of the method. Simulation studies are subsequently performed to illustrate the accuracy of the method compared to the traditional methods. Additionally, a simple and effective correction is used to deal with the boundary problem.
Keywords:Moving average model   Likelihood analysis   p-Value
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