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

## Description

Compute the average or local block entropy of a time series with block size `k`.

## Usage

 `1` ```block_entropy(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 block entropy.

## Value

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

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```# The typical usage is to provide the time series and the history length. xs <- c(0, 0, 1, 1, 1, 1, 0, 0, 0) block_entropy(xs, k = 1) # 0.9910761 # [ 0.8479969, 0.8479969, 1.169925, 1.169925, 1.169925, 1.169925, 0.8479969, # 0.8479969, 0.8479969] block_entropy(xs, k = 1, local = TRUE) block_entropy(xs, k = 2) # 1.811278 # [ 1.415037, 3.0, 1.415037, 1.415037, 1.415037, 3.0, 1.415037, 1.415037] block_entropy(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) block_entropy(xs, k = 2) # 1.936278 # [, 1] 1.415037, 2.415037, 2.415037, 2.415037, 2.415037, 2.0, 1.415037, 1.415037 # [, 2] 2.0 , 1.415037, 2.415037, 2.0, 1.415037, 2.415037, 2.0, 1.415037 block_entropy(xs, k = 2, local = TRUE) ```

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