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Combined forecasts from a linear and a nonlinear model areinvestigated for timeseries with possibly nonlinear characteristics. The forecasts arecombined by aconstant coefficient regression method as well as a time varyingmethod. Thetime varying method allows for a locally (non)linear model....
Persistent link: https://www.econbiz.de/10010324396
In this paper, we make use of state space models to investigate the presence of stochastic trends in economic time series. A model is specified where such a trend can enter either in the autoregressive representation or in a separate state equation. Tests based on the former are analogous to...
Persistent link: https://www.econbiz.de/10010324436
A major problem in applying neural networks is specifying the sizeof the network. Even for moderately sized networks the number ofparameters may become large compared to the number of data. In thispaper network performance is examined while reducing the size of thenetwork through the use of...
Persistent link: https://www.econbiz.de/10010324603
In this paper, we make use of state space models toinvestigate the presence of stochastic trends in economic time series. Amodel is specified where such a trend can enter either in the autoregressiverepresentation or in a separate state equation. Tests based on the formerare analogous to...
Persistent link: https://www.econbiz.de/10010324712
simple Monte Carlo experiment demonstrates the applicability of the approach developed in this paper. …
Persistent link: https://www.econbiz.de/10010326008
CPU. We show the use of the package and the computational gain of the GPU version, through some simulation experiments and …
Persistent link: https://www.econbiz.de/10010326164