spectral_correlation {baRulho}  R Documentation 
spectral_correlation
measures frequency spectrum correlation of signals referenced in an extended selection table.
spectral_correlation(X, parallel = 1, pb = TRUE, method = 1, cor.method = "pearson", output = "est", hop.size = 11.6, wl = NULL, ovlp = 70)
X 
object of class 'extended_selection_table' created by the function 
parallel 
Numeric vector of length 1. Controls whether parallel computing is applied by specifying the number of cores to be used. Default is 1 (i.e. no parallel computing).
If 
pb 
Logical argument to control if progress bar is shown. Default is 
method 
Numeric vector of length 1 to indicate the 'experimental design' to measure frequency spectrum correlation. Two methods are available:

cor.method 
Character string indicating the correlation coefficient to be applied ("pearson", "spearman", or "kendall", see 
output 
Character vector of length 1 to determine if an extended selection table ('est', default) or a data frame ('data.frame'). 
hop.size 
A numeric vector of length 1 specifying the time window duration (in ms). Default is 11.6 ms, which is equivalent to 512 wl for a 44.1 kHz sampling rate. Ignored if 'wl' is supplied. 
wl 
A numeric vector of length 1 specifying the window length of the spectrogram, default is NULL. If supplied, 'hop.size' is ignored. 
ovlp 
Numeric vector of length 1 specifying the percent overlap between two
consecutive windows, as in 
spectral correlation measures the similarity of two signals in the frequency domain. The function measures the spectral correlation coefficients of signals in which a reference playback has been rerecorded at increasing distances. Values range from 1 (identical frequency spectrum, i.e. no degradation) to 0. The 'signal.type' column must be used to indicate the function to only compare signals belonging to the same category (e.g. songtypes). The function will then compare each signal type to the corresponding reference signal. Two methods for calculating spectral correlation are provided (see 'method' argument). Use spectral_blur_ratio
to get spectra for plotting.
Extended selection table similar to input data, but also includes a new column ('spectrum.correlation') with the calculated frequency spectrum correlation coefficients.
Marcelo ArayaSalas (marcelo.araya@ucr.ac.cr)
ArayaSalas, M. (2020). baRulho: baRulho: quantifying habitatinduced degradation of (animal) acoustic signals in R. R package version 1.0.2
Apol, C.A., Sturdy, C.B. & Proppe, D.S. (2017). Seasonal variability in habitat structure may have shaped acoustic signals and repertoires in the blackcapped and boreal chickadees. Evol Ecol. 32:5774.
envelope_correlation
, spectral_blur_ratio
{ # load example data data("playback_est") # remove ambient selections pe < playback_est[playback_est$signal.type != "ambient", ] # method 1 spectral_correlation(X = pe) # method 2 spectral_correlation(X = pe, method = 2) }