NTS (version 1.1.1)

p_cfar: Prediction of CFAR Processes

Description

Prediction of CFAR processes.

Prediction of CFAR processes.

Usage

p_cfar(model, f, m = 3)
p_cfar(model, f, m = 3)

Arguments

model

CFAR model.

f

the functional time series data.

m

the forecast horizon.

Value

The function returns a prediction of the CFAR process.

The function returns a prediction of the CFAR process.

References

Liu, X., Xiao, H., and Chen, R. (2016) Convolutional autoregressive models for functional time series. Journal of Econometrics, 194, 263-282.

Liu, X., Xiao, H., and Chen, R. (2016) Convolutional autoregressive models for functional time series. Journal of Econometrics, 194, 263-282.

Examples

# NOT RUN {
phi_func= function(x)
{
 	return(dnorm(x,mean=0,sd=0.1))
}
y=g_cfar1(100,5,phi_func)
f_grid=y$cfar
index=seq(1,1001,by=50)
f=f_grid[,index]
est=est_cfar(f,1)
pred=p_cfar(est,f,1)
phi_func= function(x)
{
 	return(dnorm(x,mean=0,sd=0.1))
}
y=g_cfar1(100,5,phi_func)
f_grid=y$cfar
index=seq(1,1001,by=10)
f=f_grid[,index]
est=est_cfar(f,1)
pred=p_cfar(est,f,1)
# }