conditional_entropy: Conditional Entropy

Description Usage Arguments Value Examples

Description

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

Usage

1

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

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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)

ELIFE-ASU/rinform documentation built on May 26, 2019, 7:25 a.m.