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Multitaper coherence

Source: R/coupling-spectral.R
multitaperCoherence.Rd

Computes magnitude-squared coherence using multitaper spectral estimation with Discrete Prolate Spheroidal Sequences (DPSS / Slepian tapers). Multitaper estimation provides lower variance than Welch's method for short signals or when frequency resolution is critical.

Usage

multitaperCoherence(
  x,
  y = NULL,
  sr = NULL,
  nw = 4,
  k = NULL,
  freq_range = 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 an MPE.

sr

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

nw

Numeric time-bandwidth product (default 4). Controls the trade-off between frequency resolution and variance.

k

Integer number of tapers (default 2 * nw - 1).

freq_range

Optional numeric vector c(low, high) to restrict output frequencies.

modality_x, modality_y

Character modality names for MPE input.

channels_x, channels_y

Integer channel indices (default 1).

...

Currently unused.

Value

A list with components:

coherence

Numeric vector of magnitude-squared coherence values in \([0, 1]\).

frequencies

Numeric vector of corresponding frequencies in Hz.

confidence_limit

Numeric scalar giving the 95\ threshold based on the number of tapers.

References

Thomson, D. J. (1982). Spectrum estimation and harmonic analysis. Proceedings of the IEEE, 70(9), 1055–1096.

Carter, G. C. (1987). Coherence and time delay estimation. Proceedings of the IEEE, 75(2), 236–255.

See also

coherence(), crossSpectrum(), couplingAnalysis()

Examples

sr <- 500
t <- seq(0, 10, length.out = sr * 10)
x <- sin(2 * pi * 20 * t) + 0.2 * rnorm(length(t))
y <- 0.8 * sin(2 * pi * 20 * t) + 0.2 * rnorm(length(t))
result <- multitaperCoherence(x, y, sr = sr)