complexity: Calculate dynamic complexity of time series

In tkaiser86/dyncomp: Complexity of Short and Coarse-Grained Time Series

Description

A function to calculate the dynamic complexity of a series of observations, resulting from the degree of fluctuation and the degree of scattering. This measure is calculated in moving windows of a specified width, resulting in a series of values of a length equal to the length of the series of observations.

Usage

complexity(x, scaleMin, scaleMax, width = 7, measure = "complexity", rescale = FALSE)

Arguments

x	The data to be used (representing a series of observations).
scaleMin	Theoretical minimum of the data. Will default to the observed minimum of x.
scaleMax	Theoretical maximum of the data. Will default to the observed maximum of x.
width	Width of the moving window. Default is 7.
measure	Either "complexity", "fluctuation" or "distribution". Indicates which value should be returned. Default is "complexity".
rescale	If TRUE, rescales the returned values to scale minimum and maximum. This is sometimes useful for graphical interpretation or plotting. Default: FALSE.

Author(s)

Tim Kaiser <[e-mail]>

References

Kaiser, T. (2017). dyncomp: an R package for Estimating the Complexity of Short Time Series. DOI 10.17605/OSF.IO/GWTKX

Examples

t <- runif(100, 0, 10)
c <- complexity(x = t, scaleMin = 0, scaleMax = 10, width = 5, measure = "complexity",
rescale = TRUE)
plot(t, type = "l")
lines(c, col = "red", lty = 4)

tkaiser86/dyncomp documentation built on May 29, 2019, 9:54 a.m.