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dse

featherForecasts

Multiple Horizon-Step Ahead Forecasts

Description

Calculate multiple horizon-step ahead forecasts.

Usage

featherForecasts(obj, ...)
    ## S3 method for class 'TSestModel'
featherForecasts(obj, data=NULL, ...)
    ## S3 method for class 'TSdata'
featherForecasts(obj, model, ...)
    ## S3 method for class 'TSmodel'
featherForecasts(obj, data, horizon=36,
             from.periods =NULL, ...)
    is.featherForecasts(obj)

Arguments

`obj`	an object of class TSmodel.
`data`	an object of class TSdata.
`model`	an object of class TSmodel.
`from.periods`	the starting points to use for forecasts.
`horizon`	the number of periods to forecast.
`...`	for a TSmodel additional arguments are passed to `l()`

Details

Calculate multiple horizon-step ahead forecasts ie. use the samples indicated by from.periods to calculate forecasts for horizon periods. Thus, for example, the result of featherForecasts(model, data, from.periods=c(200,250,300)) would be forecasts for 1 through 36 steps ahead (the default), starting at the 200th,250th, and 300th point of outputData(data). This function assumes that inputData(data) (the exogenous variable) is as long as necessary for the most future forecast.

Value

The result is a list of class featherForecasts with elements model (a TSestModel), data, from.periods, featherForecasts. The element featherForecasts is a list with length(from.periods) elements, each of which is a tframed matrix. There is a plot method for this class.

Examples

data("egJofF.1dec93.data", package="dse")
model <- estVARXls(egJofF.1dec93.data)
pr <- featherForecasts(model, egJofF.1dec93.data)
tfplot(pr)

dse

Dynamic Systems Estimation (Time Series Package)

v2020.2-1

GPL-2

Authors

Paul Gilbert <pgilbert.ttv9z@ncf.ca>

Initial release