Bayesian Inference for Seasonal ARMA Models | ||
| The Egyptian Statistical Journal | ||
| Volume 31, Issue 1, June 1987, Pages 77-103 PDF (16.11 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/esju.1987.428903 | ||
| Authors | ||
| Samir Shaarawy; Mohamed Ali Ismail | ||
| Cairo University, Egypt | ||
| Abstract | ||
| An essential ingredient of any time series anatysis is the estimation of the modcl parameters. The main objective of this paper is to develop a convenient Rayesian technique for estimation which can be used to analyze ‘seasonal autoregressive moving average processes. The foundation of the proposed approach is to approximate the conditional likelihood by a normal-gamma distribution on the parameter space; Based on the approximated conditional likelihood function, the marginal posterior distribution of the coefficients of the model is approximated by a t distribu- tion, and the marginal posterior distribution of the model precision is approximated by a gamma distribution. The proposed technique is illustrated by some numerical examples. | ||
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