کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
998337 1481457 2011 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting correlated time series with exponential smoothing models
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
پیش نمایش صفحه اول مقاله
Forecasting correlated time series with exponential smoothing models
چکیده انگلیسی

This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection criterion is introduced into the forecasting scheme for selecting the most adequate multivariate model for describing the behaviour of the time series under study. The forecasting performance of this procedure is tested using some real examples.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 27, Issue 2, April–June 2011, Pages 252–265
نویسندگان
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