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On forecasting with univariate autoregressive processes: a bayesian approach

30 citations0/0 files storedCommunication in Statistics- Theory and Methods

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Forecasting Techniques and Applications Statistical Distribution Estimation and Applications Statistical Methods and Bayesian Inference

Abstract

Using a normal-gamma prior density for the parameters of a p-th order autoregressive process, the Bayesian predictive density of k future observations is derived and it is shown that it is the product of k univariate t densities. Our results are illustrated with one step ahead forecasts employing AR(1) and AR(2) models with a vague prior density for the parameters.

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1977Time Series Analysis: Forecasting and Control 1971Time Series Analysis Forecasting and Control.1977Forecasting Economic Time Series 1976Bayesian Forecasting 1973Multiperiod Predictions from Stochastic Difference Equations by Bayesian Methods

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