A procedure for identification of appropriate state space and ARIMA models based on time-series cross-validation
In this work, a cross-validation procedure is used to identify an appropriate Autoregressive Integrated Moving Average model and an appropriate state space model for a time series. A minimum size for the training set is specified. The procedure is based on one-step forecasts and uses different train...
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2017
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| Texto completo: | http://hdl.handle.net/10400.22/9992 |
| País: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/9992 |