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Forecasting seasonal time series data: a Bayesian model averaging approach

Vosseler, Alexander ; Weber, Enzo


A flexible Bayesian periodic autoregressive model is used for the prediction of quarterly and monthly time series data. As the unknown autoregressive lag order, the occurrence of structural breaks and their respective break dates are common sources of uncertainty these are treated as random quantities within the Bayesian framework. Since no analytical expressions for the corresponding marginal ...


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