forecastCovEstimatorsWRTtrue {dse2} | R Documentation

## Compare Forecasts Cov Relative to True Model Output

### Description

### Usage

        forecastCovEstimatorsWRTtrue(true.model, rng=NULL,
                           simulation.args=NULL,
                           est.replications = 2, pred.replications = 2,
                           discard.before = 10, horizons = 1:12, quiet =FALSE,
                           estimation.methods=NULL, compiled=.DSECOMPILED,
                           Spawn=if (exists(".SPAWN")) .SPAWN else FALSE
                           )
        is.forecastCovEstimatorsWRTtrue(obj)

### Arguments

`true.model` | An object of class TSmodel.
`estimation.methods` | A list as used by estimateModels.
`simulation.args` | an arguments to be passed to simulate.
`est.replications` | An arguments to be passed to simulate.
`pred.replications` | An arguments to be passed to simulate.
`discard.before` | An integer indicating the number of points in the beginning of forecasts to discard for calculating covariances.
`horizons` | Horizons for which forecast covariance should be calculated.
`rng` | If specified then it is used to set RNG.
`Spawn` | If TRUE then Splus For loops are used.
`quiet` | If TRUE then some messages are not printed.
`compiled` | a logical indicating if the compiled version of the code should be used. (FALSE would typically only be used for debugging.)
`obj` | an object.

### Details

Calculate the forecasts cov of models estimated from simulations of true.model with estimation methods indicated by estimation.methods (see estimateModels). This function makes multiple calls to forecastCovWRTtrue.

### Value

The returned results has element `forecastCov.true, forecastCov.zero, forecastCov.trend` containing covariances averaged over estimation replications and simulation replications (forecasts will not change but simulated data will). `forecastCov` a list of the same length as estimation.methods with each element containing covariances averaged over estimation replications and simulation replications. `estimatedModels` a list of length est.replications, with each elements as returned by estimateModels, thus each element has `multi.model` as a subelement containing models for different estimation techniques. So, eg. `estimatedModels[[2]]$multi.model[[1]]` in the result will be the model from the first estimation technique in the second replication.

### See Also

`forecastCovWRTtrue` `forecastCovEstimatorsWRTdata`

### Examples

    if(is.R()) data("eg1.DSE.data.diff", package="dse1")
    true.model <- estVARXls(eg1.DSE.data.diff) # just to have a starting model
    z <-  forecastCovEstimatorsWRTtrue(true.model,
        estimation.methods=list(estVARXls=list(max.lag=4)))

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