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http://dx.doi.org/10.5351/CSAM.2015.22.6.557

Gibbs Sampling for Double Seasonal Autoregressive Models  

Amin, Ayman A. (Department of Mathematics, Statistics and Insurance, Munofia University)
Ismail, Mohamed A. (Department of Statistics, Faculty of Economics and Political Science, Cairo University)
Publication Information
Communications for Statistical Applications and Methods / v.22, no.6, 2015 , pp. 557-573 More about this Journal
Abstract
In this paper we develop a Bayesian inference for a multiplicative double seasonal autoregressive (DSAR) model by implementing a fast, easy and accurate Gibbs sampling algorithm. We apply the Gibbs sampling to approximate empirically the marginal posterior distributions after showing that the conditional posterior distribution of the model parameters and the variance are multivariate normal and inverse gamma, respectively. The proposed Bayesian methodology is illustrated using simulated examples and real-world time series data.
Keywords
multiplicative seasonal autoregressive; double seasonality; Bayesian analysis; Gibbs sampler; internet traffic data;
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