transent: Estimating transfer entropy via copula entropy

In copent: Estimating Copula Entropy and Transfer Entropy

Estimating transfer entropy via copula entropy

Description

Estimating transfer entropy via copula entropy nonparametrically.

Usage

transent(x,y,lag=1,k=3,dt=2)

Arguments

x	data with 1 row
y	data with 1 row
lag	time lag, >0
k	kth nearest neighbour, default = 3
dt	the type of distance between samples, 1 for Eclidean distance; 2 for Maximum distance

Details

This program involves estimating transfer entropy from y to x with time lag lag via copula entropy nonparametrically. It was proposed in Ma (2019).

The algorithm first prepare the data according to lag, and then call ci for conditional independence testing.

The argument x,y are for the data with 1 row as samples from random variables. The argument lag is for time lag. The argument k and dt is used in the kNN method for estimating entropy. k is for the kth nearest neighbour (default = 3) and dt is for the type of distance between samples which has currently two value options (1 for Eclidean distance, and 2(default) for Maximum distance).

Value

The function returns the value of transfer entropy from y to x with time lag lag.

References

Ma, Jian. Estimating Transfer Entropy via Copula Entropy. arXiv preprint arXiv:1910.04375, 2019.

Examples

library(copent)
num = 300
x = rnorm(num)
y = rnorm(num)
transent(y,x,2)

copent documentation built on June 22, 2024, 9:56 a.m.