Function estimates Prediction Likelihood Score for the provided model
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The model estimated using smooth functions. This thing also accepts other models (e.g. estimated using functions from forecast package), but may not always work properly with them.
The values for the holdout part of the sample. If the model was fitted
on the data with the
Parameters passed to multicov function. The function is called in order to get the covariance matrix of 1 to h steps ahead forecast errors.
Prediction likelihood score (PLS) is based on either normal or log-normal distribution of errors. This is extracted from the provided model. The likelihood based on the distribution of 1 to h steps ahead forecast errors is used in the process.
A value of the log-likelihood.
Ivan Svetunkov, firstname.lastname@example.org
distribution. IEEE Signal Processing Letters. 13 (5): 300-303. doi: 10.1109/LSP.2006.870353 - this is not yet used in the function.
Snyder, R. D., Ord, J. K., Beaumont, A., 2012. Forecasting the intermittent demand for slow-moving inventories: A modelling approach. International Journal of Forecasting 28 (2), 485-496.
Kolassa, S., 2016. Evaluating predictive count data distributions in retail sales forecasting. International Journal of Forecasting 32 (3), 788-803..
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