Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach
Ismail, M., Gargoum, A. (2000). Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach. EKB Journal Management System, 44(2), 159-170. doi: 10.21608/esju.2000.313832
Mohamed A. Ismail; Ali S. Gargoum. "Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach". EKB Journal Management System, 44, 2, 2000, 159-170. doi: 10.21608/esju.2000.313832
Ismail, M., Gargoum, A. (2000). 'Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach', EKB Journal Management System, 44(2), pp. 159-170. doi: 10.21608/esju.2000.313832
Ismail, M., Gargoum, A. Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach. EKB Journal Management System, 2000; 44(2): 159-170. doi: 10.21608/esju.2000.313832

Testing Linearity Against Asymmetric Moving Average Models: A Bayesian Approach

The Egyptian Statistical Journal
Article 4, Volume 44, Issue 2, December 2000, Page 159-170  XML PDF (5.52 MB)
Document Type: Original Article
DOI: 10.21608/esju.2000.313832
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Authors
Mohamed A. Ismail* 1; Ali S. Gargoum* 2
1Department of Statistics, UAE University
2Department of Statistics UAE University
Abstract
Bayesian analysis for Asymmetric Moving Average (asMA) models is introduced. Using informative as well as noninformative priors, the posterior density of the model coefficients is approximated by a multivariate t distribution. A direct approach to test the hypothesis of symmetry versus the alternative of asymmetry is developed. Two simulated examples with a real data are presented to illustrate the proposed technique.
 
Keywords
Asymmetry; Posterior Distribution; Multivariate T; US GNP
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