Predictions of Time Series

František Štulajter ()
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František Štulajter: Comenius University, Department of Statistics, FMFI UK

Chapter 4 in Predictions in Time Series Using Regression Models, 2002, pp 147-195 from Springer

Abstract: 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).

Keywords: Time Series; Covariance Matrix; Random Vector; Covariance Function; Modeling Time Series (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-3629-8_4

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DOI: 10.1007/978-1-4757-3629-8_4

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