plot_autocovariance: Generate a 3D plot of the autocovariance surface of a given...

In fdaACF: Autocorrelation Function for Functional Time Series

Description

Obtain a 3D plot of the autocovariance surfaces of a given functional time series. This visualization is useful to detect any kind of dependency between the discretization points of the series.

Usage

plot_autocovariance(fun.autocovariance, lag = 0, ...)

Arguments

fun.autocovariance	A list obtained by calling the function obtain_autocovariance.
lag	An integer between 0 and nlags, indicating the lagged autocovariance function to be plotted. By default 0.
...	Further arguments passed to the persp function.

Examples

# Example 1

N <- 100
v <- seq(from = 0, to = 1, length.out = 10)
sig <- 2
bbridge <- simulate_iid_brownian_bridge(N, v, sig)
nlags <- 1
lagged_autocov <- obtain_autocovariance(Y = bbridge,nlags = nlags)
plot_autocovariance(lagged_autocov,1)


# Example 2

N <- 500
v <- seq(from = 0, to = 1, length.out = 50)
sig <- 2
bbridge <- simulate_iid_brownian_bridge(N, v, sig)
nlags <- 4
lagged_autocov <- obtain_autocovariance(Y = bbridge,nlags = nlags)
opar <- par(no.readonly = TRUE)
par(mfrow = c(1,5))
for(k in 0:nlags){
   plot_autocovariance(lagged_autocov,k)
}
par(opar)

fdaACF documentation built on Oct. 23, 2020, 8:05 p.m.