bispectrum function

Estimate bispectrum from time series data.

Estimate bispectrum from time series data.

Estimate bispectrum from real- or complex-valued time series data.

bispectrum( data, window_function = NULL, mc = FALSE, mc_cores = getOption("mc.cores", 2L) )

Arguments

  • data: Given time series, as a data frame or matrix with which columns correspond to sampled stretches.

  • window_function: A window function's name for tapering. Defaults to NULL ("no tapering").

    Currently the following window functions are available: Hamming window ("hamming"), Hann window ("hann"), and Blackman window ("blackman").

  • mc: If TRUE, calculation is done in parallel computation. Defaults to FALSE.

  • mc_cores: The number of cores in use for parallel computation, passed parallel::mcmapply() etc. as mc.cores.

Returns

A data frame including the following columns:

  • f1:: The first elements of frequency pairs.
  • f2:: The second elements of frequency pairs.
  • value:: The estimated bispectrum at each frequency pair.

Examples

f <- function(x) { sin(2 * x) + sin(3 * x + 1) + sin(2 * x) * sin(3 * x + 1) } v <- sapply(seq_len(1280), f) + rnorm(1280) m <- matrix(v, nrow = 128) bs1 <- bispectrum(m) bs2 <- bispectrum(m, "hamming") bs3 <- bispectrum(m, "blackman", mc = TRUE, mc_cores = 1L)

References

Brillinger, D.R. and Irizarry, R.A. "An investigation of the second- and higher-order spectra of music." Signal Processing, Volume 65, Issue 2, 30 March 1998, Pages 161-179.

  • Maintainer: Takeshi Abe
  • License: GPL-3
  • Last published: 2024-05-17