Two sided analysis of variance with a latent time series
AbstractMany real life regression problems exhibit some kind of calender time dependency and it is often of interest to predict the behavior of the regression function along this calender time direction. This can be formulated as a regression model with an added latent time series and the task is to be able to analyse this series. In this paper we engage this through a two step procedure, firstly we treat the time dependent elements as parameters and estimate them in the two-sided analysis of variance setup, secondly we use the estimated time series as predictor of the latent time series. An application to risk theory is discussed.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2004-W25.
Date of creation: 01 Oct 2004
Date of revision:
Regression; Time Series; Risk Theory;
Other versions of this item:
- Lars Hougaard Hansen & Bent Nielsen & Jens Perch Nielsen, 2004. "Two sided analysis of variance with a latent time series," Economics Papers 2004-W25, Economics Group, Nuffield College, University of Oxford.
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