simulate_iid_brownian_motion: Simulate a FTS from a brownian motion process
In fdaACF: Autocorrelation Function for Functional Time Series

Description Usage Arguments Value Examples

Generate a functional time series from a Brownian Motion process. Each functional observation is discretized in the points indicated in v. The series obtained is i.i.d. and does not exhibit any kind of serial correlation

1 2	simulate_iid_brownian_motion(N, v = seq(from = 0, to = 1, length.out = 100), sig = 1)

`N`	The number of observations of the simulated data.
`v`	Discretization points of the curves, by default `seq(from = 0, to = 1, length.out = 100)`.
`sig`	Standard deviation of the Brownian Motion process, by default `1`.

Return the simulated functional time series as a matrix.

N <- 100
v <- seq(from = 0, to = 1, length.out = 20)
sig <- 2
bmotion <- simulate_iid_brownian_motion(N, v, sig)
matplot(v,t(bmotion), type = "l", xlab = "v", ylab = "Value")