FCVARforecast: Forecasts with the FCVAR Model

In FCVAR: Estimation and Inference for the Fractionally Cointegrated VAR

Forecasts with the FCVAR Model

Description

FCVARforecast calculates recursive forecasts with the FCVAR model.

Usage

FCVARforecast(x, model, NumPeriods)

Arguments

x	A matrix of variables to be included in the system. The forecast will be calculated using these values as starting values.
model	A list of estimation results, just as if estimated from FCVARest. The parameters in model can also be set or adjusted by assigning new values.
NumPeriods	The number of time periods in the simulation.

Value

A NumPeriods \times p matrix xf of forecasted values.

See Also

FCVARoptions to set default estimation options. FCVARestn for the specification of the model. FCVARforecast calls FracDiff and Lbk to calculate the forecast.

Other FCVAR auxiliary functions: FCVARlikeGrid(), FCVARsimBS(), FCVARsim(), FracDiff(), plot.FCVAR_grid()

Examples

opt <- FCVARoptions()
opt$gridSearch   <- 0 # Disable grid search in optimization.
opt$dbMin        <- c(0.01, 0.01) # Set lower bound for d,b.
opt$dbMax        <- c(2.00, 2.00) # Set upper bound for d,b.
opt$constrained  <- 0 # Impose restriction dbMax >= d >= b >= dbMin ? 1 <- yes, 0 <- no.
x <- votingJNP2014[, c("lib", "ir_can", "un_can")]
opt1 <- opt
opt1$R_Alpha <- matrix(c(0, 1, 0), nrow = 1, ncol = 3)
m1r4 <- FCVARestn(x, k = 2, r = 1, opt1)
xf <- FCVARforecast(x, m1r4, NumPeriods = 12)

FCVAR documentation built on May 5, 2022, 9:06 a.m.