outOfSample.forecastCovEstimatorsWRTdata {dse2} | R Documentation

## Calculate Out-of-Sample Forecasts

### Description

Calculate out-of-sample forecasts.

### Usage

        outOfSample.forecastCovEstimatorsWRTdata(data, zero=FALSE, trend=FALSE,
                           estimation.sample=.5, horizons=1:12,quiet=FALSE,
                           estimation.methods=NULL, compiled=.DSECOMPILED)

### Arguments

`data` | an object of class TSdata.
`estimation.methods` | a list as used by estimateModels.
`zero` | if TRUE then forecastCov is also calculated for a forecast of zero.
`trend` | if TRUE then forecastCov is also calculated for a forecast of a linear trend.
`estimation.sample` | indicates the portion of the data to use for estimation. If estimation.sample is an integer then it is used to indicate the number of points in the sample to use for estimation. If it is a fracton it is used to indicate the portion of points to use for estimation. The remainder of the sample is used for evaluating forecasts.
`horizons` | horizons for which forecast covariance should be calculated.
`quiet` | if TRUE then estimation information is not printed.
`compiled` | a logical indicating if compiled code should be used. (Usually true except for debugging.)

### Details

The data is slpit into a sub-sample used for estimation and another sub-sample used for calculating the forecast covariance.

### Value

An object as returned by forecastCovEstimatorsWRTdata.

### See Also

`forecastCovEstimatorsWRTdata`, `forecastCovEstimatorsWRTtrue`, `estimateModels`

### Examples

    if(is.R()) data("eg1.DSE.data.diff", package="dse1")
    z <-  outOfSample.forecastCovEstimatorsWRTdata(eg1.DSE.data.diff,
               estimation.methods=list(estVARXls=list(max.lag=4)))

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