| transent {copent} | R Documentation |
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)