Object Reference : Object View and Procedure Reference : Series
  
 
forceval
Evaluate different forecasts of a series, and perform the forecast combination test.
Syntax
series.forceval(options) forecast_data
You should specify the forecast data to be evaluated by entering a list of objects as forecast_data. The list may be a list of series objects, a group object, a series naming pattern (such as “f*” to indicate all series starting with the letter “F”), or a list of equation objects.
If a list of equations is entered, EViews will automatically forecast from those equation objects over the evaluation sample (the current workfile sample).
Options
 
mean
Include the Mean averaging method.
trmean
Include the Trimmed mean averaging method.
median
Include the Median averaging method.
ols
Include the Least-squares averaging method.
mse
Include the Mean Square Error averaging method.
mseranks
Include the MSE ranks averaging method.
aic
Include the Smoothed AIC weights averaging method. Only applicable if forecast_data is a list of equation objects.
sic
Include the Bayesian model averaging method. Only applicable if forecast_data is a list of equation objects.
trim=num
Set the level of trimming for the Trimmed mean method. Num should be a number between 1 and 100. Only applicable if the “trmean” option is used.
msepwr=int
Set the power to which the MSE values are raised in the MSE ranks method. Only applicable if the “mseranks” option is used.
s
Use a static (rather than dynamic) forecast when computing the forecasts over the training sample. Only applicable if forecast_data is a list of equation objects.
trainsmpl=arg
Specify the sample used for calculating the averaging weights. Only applicable if the “ols”, “mse”, “mseranks”, “aic” or “sic” options are used.
testname=arg
Save the combination test statistics into a matrix named arg.
statname=arg
Save the names of the best performing forecasts into an svector named arg.
Example
The commands
wfopen elecdmd.wf1
elecdmd.forcval(trainsmpl="2012M1 2012M12", mean, mse, mseranks, msepwr=2) elecf_fe*
open the workfile elecdmd.wf1 and then perform forecast evaluation using the actual series ELECDMD, and the forecast series specified by the naming pattern ELECF_FE*.
The averaging methods Mean, MSE and MSE Ranks are used, with the power of the MSE Ranks method set at “2”. A training sample of 2012M1 to 2012M12 is used to calculate the weights in the MSE and MSE Ranks methods.
Cross-references
See “Forecast Evaluation” for additional discussion.
See also Series::forcavg.