vars (version 0.1.7)

predict.varest: Predict method for objects of class varest

Description

Forecating a VAR object of class varest with confidence bands.

Usage

## S3 method for class 'varest':
predict(object, ..., n.ahead = 10, ci = 0.95)

Arguments

object

An object of class varest; generated by VAR().

n.ahead

An integer specifying the number of forecast steps.

ci

The forecast confidence interval

...

Currently not used.

Value

• A list with class attribute varprd holding the following elements:
• fcst
  A list of matrices per endogenous variable containing the forecasted values with lower and upper bounds as well as the confidence interval.
• endog
  Matrix of the in-sample endogenous variables.
• model
  The estimated VAR object.

encoding

latin1

concept

• VAR
• Vector autoregressive
• Forecasts of VAR
• Prediction of VAR

Details

The n.ahead forecasts are computed recursively for the estimated VAR, beginning with $h = 1, 2, \ldots, n.ahead$: $$\bold{y}_{T+1 | T} = A_1 \bold{y}_T + \ldots + A_p \bold{y}_{T+1-p} + C D_{T+1}$$ The variance-covariance matrix of the forecast errors is a function of $\Sigma_u$ and $\Phi_s$.

References

Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton. L�tkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.

See Also

VAR, plot.varprd, fanchart

Examples

data(Canada)
var.2c <- VAR(Canada, p = 2, type = "const")
predict(var.2c, n.ahead = 8, ci = 0.95)