Getting started

Andreas M. Brandmaier

2023-05-10

R Markdown

Load the library.

library(pdcsync)

Simulate two time series. The first time series is generated from an autoregressive process. The second time series is a time-shifted version of the first one with some added minimal noise. There is an induced complete break of symmetry between time points 200 and 400.

N <- 1000

t1 <- arima.sim(model = list(ar = 0.2), n = N)

# t2 is later than t1; t1 leads
t2 <- c(t1[4:(length(t1))], 0, 0, 0) + rnorm(N, 0, 0.001)

# no synchrony between 200 and 400
t2[200:400] <- runif(201, 0, 1)

Call the synchronization detection:

sync <- pdcsync(t1, t2)

Plot the synchronization profile

plot(sync)
## Warning: Transformation introduced infinite values in discrete y-axis

Plot the synchronization profile using the extended plot method:

syncplot(sync)
## Don't know how to automatically pick scale for object of type <ts>. Defaulting
## to continuous.
## Warning: Transformation introduced infinite values in discrete y-axis

Compute an (experimental) global synchronisation measure (between 0 and 1, with higher values indicating stronger synchrony).

## [1] 0.7419336

Now, we further reduce the synchronisation and re-run the algorithm again.

# no synchrony between 200 and 400
t2[200:600] <- runif(201, 0, 1)
## Warning in t2[200:600] <- runif(201, 0, 1): number of items to replace is not a
## multiple of replacement length
sync <- pdcsync(t1, t2)

Plot the synchronization profile using the extended plot method:

syncplot(sync)
## Don't know how to automatically pick scale for object of type <ts>. Defaulting
## to continuous.
## Warning: Transformation introduced infinite values in discrete y-axis

Compute an (experimental) global synchronisation measure (between 0 and 1, with higher values indicating stronger synchrony). This value is lower than before because global synchronisation decreased.

## [1] 0.5348691