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Sliding-window cross-correlation

Source: R/coupling-timedom.R
slidingCrossCorrelation.Rd

Computes cross-correlation in sliding (overlapping) windows to track how time-domain coupling varies over time. For each window position, crossCorrelation is called and the results are assembled into a matrix.

Usage

slidingCrossCorrelation(
  x,
  y = NULL,
  sr = NULL,
  window_sec = 1,
  step_sec = 0.5,
  max_lag = NULL,
  modality_x = NULL,
  modality_y = NULL,
  channels_x = 1L,
  channels_y = 1L
)

Arguments

x

Numeric vector, PhysioExperiment, or MultiPhysioExperiment.

y

Numeric vector or PhysioExperiment, or NULL when x is a MultiPhysioExperiment.

sr

Numeric sampling rate in Hz (required when x/y are numeric).

window_sec

Numeric window length in seconds (default 1).

step_sec

Numeric step size in seconds (default 0.5).

max_lag

Integer maximum lag in samples for each window. If NULL, defaults to floor(window_samples / 4).

modality_x

Character modality name in MPE for the x signal.

modality_y

Character modality name in MPE for the y signal.

channels_x

Integer which channel to extract from x (default 1).

channels_y

Integer which channel to extract from y (default 1).

Value

A named list with components:

correlations

Numeric matrix of dimensions (n_windows x n_lags) containing cross-correlation values.

times

Numeric vector of window centre times in seconds.

lags

Integer vector of lag values in samples.

peak_lags

Numeric vector of peak lags (in samples) for each window.

peak_correlations

Numeric vector of peak correlation values for each window.

References

Chatfield, C. (2004). The Analysis of Time Series: An Introduction (6th ed.). Chapman & Hall/CRC.

See also

crossCorrelation(), plotCouplingTimecourse(), couplingAnalysis()

Examples

sr <- 500
set.seed(1)
x <- rnorm(5000)
y <- c(rep(0, 10), x[1:4990])
result <- slidingCrossCorrelation(x, y, sr = sr,
                                   window_sec = 1, step_sec = 0.5)
dim(result$correlations)
#> [1]  19 251
result$peak_lags
#>  [1] -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10