PsiForecast()

PsiForecast(Model, Input_Data, [Simulate], Num_Forecasts, [Header])

Computes the forecasts for Input_Data using a Time Series model stored in PMML format.  Note:  If using a version of Excel that does not support Dynamic Arrays, this formula must be entered as an Excel array. 

Model:  Range containing the stored Times Series model in PMML format.  

Input_Data:  Range containing the new Time Series data for computing the forecasts. Range must contain a header with the time series name and a sufficient number of records for the forecasting with a given model.

Simulate:  If True, the forecasts are adjusted with random normally distributed errors. If False or omitted, the forecasts will be deterministic.

Num_forecasts:  Enter the number of desired forecasts.

Header:  (Optional)  If True, a heading is inserted above the returned forecasts.  If False or omitted, no heading is inserted.  

Note:  In Analytic Solver Cloud and in newer versions of desktop Excel, PsiForecast() returns a Dynamic Array.  The contents of the Dynamic Array will "spill" down the column.  If a nonblank cell is "blocking" the contents of the Dynamic Array, PsiForecast() will return #SPILL until such time as the blockage is removed. 

Output: A single column containing the header and forecasts for input time series. The number of produced forecasts is determined by the number of selected cells in the array-formula entry. 

Supported Models:

Arima

Exponential Smoothing

Double Exponential Smoothing

Holt Winters Smoothing

Previous related Psi Scoring functions: PsiForecastARIMA, PsiForecastExp, PsiForecastDoubleExp, PsiForecastMovingAvg, PsiForecastHoltWinters

Each forecasting method requires a minimum number of initial points. See the chart below for each forecasting method's requirements. 

**Adding a number of data points equal to the Number of Periods (as shown on the Time Series – ARIMA dialog) to the Minimum # of Initial Points when Simulate = True is recommended when calling PsiForecast() with Simulate = True.