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Full Bayesian analysis of seasonal autoregressive models under scale-mixtures of normal errors

In this paper we present a full Bayesian analysis of multiplicative seasonal autoregressive models under SMN errors.

Testing Random Effects in Linear Mixed Regression Models

This article reviews existing tests for the random effects, and then it presents a comparison using a simulation study to examine the performance of these tests.

Bayesian modeling and forecasting of seasonal autoregressive models with scale-mixtures of normal errors

In this paper we present a Bayesian estimation and prediction of multiplicative seasonal autoregressive models under SMN errors.

Bayesian estimation of seasonal autoregressive models with scale-mixtures of normal errors

In this paper we present a Bayesian estimation of multiplicative seasonal autoregressive models under SMN errors.

Gibbs sampler for Bayesian prediction of triple seasonal autoregressive processes

In this paper we use the Gibbs sampling algorithm to present a Bayesian prediction of multiplicative triple seasonal autoregressive (TSAR) models.

Full Bayesian Analysis of Triple Seasonal Autoregressive Models

In this paper we use the Gibbs sampling algorithm to present a full Bayesian analysis of multiplicative triple seasonal autoregressive (TSAR) models.

Full Bayesian analysis of double seasonal autoregressive models with real applications

In this paper we use the Gibbs sampling algorithm to present a full Bayesian analysis to multiplicative double seasonal autoregressive (DSAR) models.

Analysing the Factors Affecting the Cost of Health Insurance in Egyptian Market

This research paper aims to analyze the factors influencing the cost of health insurance in Egypt, with a focus on the private healthcare sector.

Bayesian Identification Procedure for Triple Seasonal Autoregressive Models

In this paper, we present a Bayesian procedure to identify the order of TSAR models.

Bayesian Subset Selection of Seasonal Autoregressive Models

In this paper, we introduce a Bayesian method for selecting the most promising subset of the seasonal autoregressive (SAR) models.