predict.sfar {Rsfar}

Prediction of an SFAR model

Description

Compute h-step-ahead prediction for an SFAR(1) model. Only the h-step predicted function is returned, not the predictions for 1,2,...,h.

Usage

## S3 method for class 'sfar'
predict(object, h, ...)

Arguments

object

an 'sfar' object containing a fitted SFAR(1) model.

h

number of steps ahead to predict.

...

Other parameters, not currently used.

Value

An object of class fda.

Examples

# Generate Brownian motion noise
N <- 300 # the length of the series
n <- 200 # the sample rate that each function will be sampled
u <- seq(0, 1, length.out = n) # argvalues of the functions
d <- 45 # the number of bases
basis <- create.fourier.basis(c(0, 1), d) # the basis system
sigma <- 0.05 # the std of noise norm
Z0 <- matrix(rnorm(N * n, 0, sigma), nrow = n, nc = N)
Z0[, 1] <- 0
Z_mat <- apply(Z0, 2, cumsum) # N standard Brownian motion
Z <- smooth.basis(u, Z_mat, basis)$fd

# Simulate random SFAR(1) data
kr <- function(x, y) {
  (2 - (2 * x - 1)^2 - (2 * y - 1)^2) / 2
}
s <- 5 # the period number
X <- rsfar(kr, s, Z)
plot(X)

# SFAR(1) model parameter estimation:
Model1 <- sfar(X, seasonal = s, kn = 1)

# Forecasting 3 steps ahead
fc <- predict(Model1, h = 3)
plot(fc)