Abstract
The problem of the prediction of time series belongs to the most important problems of the statistical inference of time series. There are many approaches to these problems, possibly the best known is that based on the Box-Jenkins methodology of modeling time series by using ARMA and ARIMA models, another approach is based on modeling time series by regression models. It can be said that the Box-Jenkins methodology is the most popular and there exists a lot of literature on different levels dealing with this approach. We refer to Box and Jenkins (1976), Brockwell and Davis (1987), (1996), and many others. The approach based on regression models, known as kriging in engineering literature, mainly in geostatistics, can be found in David (1977), Journel and Hiiijbregts (1978), Ripley (1981), and in Christensen (1987), (1991).
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© 2002 Springer Science+Business Media New York
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Štulajter, F. (2002). Predictions of Time Series. In: Predictions in Time Series Using Regression Models. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3629-8_4
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DOI: https://doi.org/10.1007/978-1-4757-3629-8_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-2965-5
Online ISBN: 978-1-4757-3629-8
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