Packages

trait ForecasterMat extends AnyRef

The ForecasterMat trait add the 'forecast' method to PredictorMat subclasses facilitating the adaption of predictive modeling techniques such as Regression for use in forecasting, viz. Regression4TS. Note: for forecasting, cross-validation needs to be of the rolling-validation form.

See also

the 'crossValidate' method in RollingValidation

Linear Supertypes
AnyRef, Any
Known Subclasses
ELM_3L1_4TS, NeuralNet_3L1_4TS, NeuralNet_3L1_4TSy, QuadRegression4TS, QuadRegression4TSy, QuadXRegression4TS, QuadXRegression4TSy, Regression4TS, Regression4TSy
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  1. ForecasterMat
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Abstract Value Members

  1. abstract def forecast(xe: MatriD, t: Int, h: Int = 1): Double

    Produce a forecast for 'h' steps ahead into the future from current time 't'.

    Produce a forecast for 'h' steps ahead into the future from current time 't'.

    xe

    the relevant (optionally expanded) input/data matrix

    t

    the "current" time to be forecasted, e.g., h = 1 => current, h = 2 => future

    h

    the forecasting horizon, number of steps ahead to produce forecast

Concrete Value Members

  1. def forecastAll(xe: MatriD = null, h: Int = 1): VectoD

    Forecast values for all time points using 1 through 'h'-steps ahead forecasts.

    Forecast values for all time points using 1 through 'h'-steps ahead forecasts. Return a vector of forecasts for all time points.

    xe

    the relevant (optionally expanded) input/data matrix

    h

    the forecasting horizon, number of steps ahead to produce forecasts