periodogram: Computes periodograms

In zeitgebr: Analysis of Circadian Behaviours

Description

This function builds periodograms, with one of several methods, for each individual of a behavr table

Usage

periodogram(var, data, period_range = c(hours(16), hours(32)),
  resample_rate = 1/mins(15), alpha = 0.01, FUN = chi_sq_periodogram,
  ...)

Arguments

var	variable to analyse
data	behavr table
period_range	vector of size 2 defining minimal and maximal range of period to study (in seconds)
resample_rate	frequency to resample (up or down) the data at (in hertz)
alpha	significance level
FUN	function used to compute periodogram (see periodogram_methods)
...	additional arguments to be passed to FUN

Value

A behavr::behavr table. In addition to the metadata, it contains data that encodes a periodogram (i.e. power vs period). The data contains the columns:

• power – the power the or equivalent (according to FUN)

• period – the period at which power is computed (in seconds)

• p_value – the p value associated to the power estimation

• signif threshold – the threshold above which power is considered significant

References

• zeitgebr tutorial – the relevant rehtomics tutorial

See Also

• periodogram_methods – the list of built-in methods

• find_peaks – to find peaks in the periodogram

• ggetho::ggperio – to plot periodograms

Examples

data(dams_sample)
# only four individuals for the sake of the example
dt <- dams_sample[xmv(region_id) %in% c(1, 7, 21, 31)]
pdt <- periodogram(activity, dt, FUN = ls_periodogram, oversampling = 4)
pdt <- periodogram(activity, dt, FUN = chi_sq_periodogram)

require(ggetho)
ggperio(pdt, aes(colour=period_group)) + stat_pop_etho()

zeitgebr documentation built on April 25, 2020, 5:07 p.m.