conditional_entropy: Conditional Entropy

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

Description

Compute the average or the local conditional entropy between two time series. This function expects the condition to be the first argument.

Usage

conditional_entropy(xs, ys, local = FALSE)

Arguments

xs	Vector specifying a time series drawn from the conditional distribution.
ys	Vector specifying a time series drawn from the target distribution.
local	Boolean specifying whether to compute the local conditional entropy.

Value

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

Examples

xs <- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1)
ys <- c(0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1)
conditional_entropy(xs, ys)      # 0.5971072
conditional_entropy(ys, xs)      # 0.5077571

# [1] 3.0, 3.0, 0.1926451, 0.1926451, 0.1926451, 0.1926451, 0.1926451, 0.1926451,
#     0.1926451, 0.1926451, 0.1926451, 0.1926451, 0.1926451, 0.1926451, 0.1926451,
#     0.1926451, 0.4150375, 0.4150375, 0.4150375, 2.0
conditional_entropy(xs, ys, local = TRUE)

# [1] 1.32192809, 1.32192809, 0.09953567, 0.09953567, 0.09953567, 0.09953567,
#     0.09953567, 0.09953567, 0.09953567, 0.09953567, 0.09953567, 0.09953567,
#     0.09953567, 0.09953567, 0.09953567, 0.09953567, 0.73696559, 0.73696559,
#     0.73696559,  3.9068906
conditional_entropy(ys, xs, local = TRUE)

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