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Cross-validated

The cross-validated calculation option fits a CCA, PCR, or MLR model using all data within the training period. This model is used to make any forecasts using predictor data supplied in the "forecast file". The option also produces cross-validated forecasts for each year in the training period. (Note that these cross-validated forecasts, and therefore the available validation statistics, are purely deterministic: no uncertainty estimates are generated. If a set of past probabilistic forecasts is required, perhaps with accompanying verification statistics, the retroactive option should be selected.) At each cross-validation step k consecutive years are omitted from the training period, where k is the "length of the cross-validation window". The model is then completely reconstructed, including recalculating the principal components, and redefining the category thresholds, and the middle year of the years omitted from the training sample is forecast. This process is repeated for each year. Towards the beginning and end of the training period the cross-validation window is looped to ensure that exactly k years are always omitted. For example, if k = 5, when forecasting the first year, the first three years are omitted together with the last two; when forecasting the second year, the first four years are omitted together with the last one.

The cross-validated forecasts are made available for output to a file, and for performance analyses within CPT. Note that all the information regarding the definitions of the principal components and CCA modes (where applicable) is based on the results using all the data within the training period, but all the results regarding the performance of the model (validation) are based on the cross-validated forecasts.


 
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