# 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

 `1` ```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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```# 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.