stplot: Plot for space-time series autocorrelation functions

In starma: Modelling Space Time AutoRegressive Moving Average (STARMA) Processes

Description

stplot renders a nice 2d plot for autocorrelation functions.

Usage

stplot(acf, ci, call, ggplot=T)

Arguments

acf	a matrix containing the autocorrelation functions of a given space-time series: row-wise should be the temporal observations, with each column corresponding to a space lag.
ci	confidence intervals for the autocorrelation functions.
call	the name of the plot.
ggplot	a boolean indicating whether to use ggplot2 functions (they are recommended).

Details

This function plots the calculated autocorrelation functions of a space-time series.

In practice, the user should not use this function, as it is being called automatically when using stacf or stpacf. The confidence intervals for the autocorrelation functions are approximated by

var(rho[lk]) = 1 / (N*(T-k))

where N is the number of sites, and T the number of temporal observations.

Value

NULL

Author(s)

Felix Cheysson

References

- Pfeifer, P., & Deutsch, S. (1981). Variance of the Sample Space-Time Autocorrelation Function. Journal of the Royal Statistical Society. Series B (Methodological), 43(1): 28-33.

Examples

data(nb_mat)	# Get neighbourhood matrices

# Simulate a STARMA model
eps <- matrix(rnorm(94*200), 200, 94)
sim <- eps
for (t in 3:200) {
	sim[t,] <- (.4*diag(94) + .25*blist[[2]]) %*% sim[t-1,] +
		(.25*diag(94)                ) %*% sim[t-2,] +
		(            - .3*blist[[2]]) %*% eps[t-1,] +
		eps[t, ]
}

sim <- sim[101:200,]
sim <- stcenter(sim)	# Center and scale the dataset

# Autocorrelation functions
sim.stacf <- stacf(sim, blist, plot=FALSE)

# Plot the autocorrelation function
stplot(sim.stacf, 2 / sqrt(nrow(sim) * ncol(sim)), "stacf(sim, blist)")

Example output

starma documentation built on May 2, 2019, 1:26 p.m.