select.forecast.cov {dse2}R Documentation

Select Forecast Covariances Meeting Criteria

Description

Select forecast covariances meeting given criteria.

Usage

    select.forecast.cov(obj, select.series=1, 
    select.cov.best=1,
    select.cov.bound=NULL,
    ranked.on.cov.bound=NULL,
    verbose=T)

Arguments

obj An object as returned by mine.strip.
select.series An indication of series to which the tests should be applied.
select.cov.best The number of 'best' forecasts to select.
select.cov.bound A bound to use as criteria for selection.
verbose If verbose=T then summary results are printed.

Details

Select models with forecast covariance for select.series meeting criteria. The default select.cov.best=1 selects the best model at each horizon. select.cov.best=3 would select the best 3 models at each horizon. If select.cov.bound is not NULL then select.cov.best is ignored and any model which is better than the bound at all horizons is selected. select.cov.bound can be a vector of the same length as select.series, in which case corresponding elements are applied to the different series.

Value

The returned result is a forecast.cov object like obj, but filtered to remove models which do not meet criteria.

See Also

min.forecast.cov, exclude.forecast.cov

Examples

if(is.R()) data("eg1.DSE.data.diff", package="dse1")
z <- mine.strip(eg1.DSE.data.diff, essential.data=c(1,2),
                   estimation.methods=list(est.VARX.ls=list(max.lag=3)))
z <-  select.forecast.cov(z)
tfplot(select.forecast.cov(z, select.cov.bound=20000))
tfplot(select.forecast.cov(z, select.cov.best=1))