entropy_rate: Entropy Rate

In rinform: An R Wrapper of the 'Inform' C Library for Information Analysis of Complex Systems

Description

Compute the average or local entropy rate of a time series with history length k.

Usage

entropy_rate(series, k, local = FALSE)

Arguments

series	Vector or matrix specifying one or more time series.
k	Integer giving the history length.
local	Boolean specifying whether to compute the local entropy rate.

Value

Numeric giving the average entropy rate or a vector giving the local entropy rate.

Examples

# The typical usage is to provide the time series and the history length. 
xs <- c(0, 0, 1, 1, 1, 1, 0, 0, 0)
entropy_rate(xs, k = 2) #0.6792696
# [1] 1.0, 0.0, 0.5849625, 0.5849625, 1.5849625, 0.0, 1.0
entropy_rate(xs, k = 2, local = TRUE)

# Multiple Initial Conditions
xs      <- matrix(0, nrow = 9, ncol = 2)
xs[, 1] <- c(0, 0, 1, 1, 1, 1, 0, 0, 0)
xs[, 2] <- c(1, 0, 0, 1, 0, 0, 1, 0, 0)
entropy_rate(xs, k = 2)         # 0.6253491

# [, 1] 0.4150375, 1.5849625, 0.5849625, 0.5849625, 1.5849625, 0.0, 2.0
# [, 2] 0.0, 0.4150375, 0.5849625, 0.0, 0.4150375, 0.5849625, 0.0
entropy_rate(xs, k = 2, local = TRUE)

rinform documentation built on April 1, 2018, 12:12 p.m.