entropy: Entropy Computation

In bigdatadist: Distances for Machine Learning and Statistics in the Context of Big Data

Description

This function allows you to compute the family of alpha entropy as stated in Martos et al (2018).

Usage

entropy(X,alpha=2,k.neighbor,scale=FALSE) 

Arguments

X	data in a matrix where variables are in columns and observations are in rows.
alpha	a parameter defining the entropy function.
k.neighbor	number of neighbour points to consider in the computation of entropy.
scale	logical variable indicating if scaling is required.

Details

The function computes the alpha entropy and the local alpha entropy (see reference for further details) of a data set using a non parametric density estimator.

Value

local.entropy	local entropy relative to each point in the sample.
entropy	estimated entropy.

References

Martos, G. et al (2018): Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection. Entropy 20(1): 33 (2018).

Examples

require(MASS);
data = mvrnorm(100,c(0,0),diag(2));
entropy(data, alpha = 2, k.neighbor = 10, scale = FALSE)

bigdatadist documentation built on May 2, 2019, 11:06 a.m.