1998
A model selection strategy for time series with increasing seasonal variation
Publication
Publication
International Journal of Forecasting p. 405- 414
We propose a model selection strategy for time series with increasing seasonal variation. This strategy amounts to a selection of the most appropriate differencing filter to obtain a stationary time series without using a Box-Cox transformation. Hence, it is based on a sequence of tests for nonseasonal and seasonal unit roots. Through Monte Carlo replications, we provide new tables of critical values for the various test statistics. We apply our methods, which can be automated, to six example series and find that the results compare favorably to those of an expert.
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doi.org/10.1016/S0169-2070(98)00041-7, hdl.handle.net/1765/2145 | |
International Journal of Forecasting | |
Organisation | Erasmus School of Economics |
Franses, P. H., & Koehler, A. (1998). A model selection strategy for time series with increasing seasonal variation. International Journal of Forecasting, 405–414. doi:10.1016/S0169-2070(98)00041-7 |