te_disc: Discrete Transfer Entropy

In NlinTS: Models for Non Linear Causality Detection in Time Series

Description

Discrete Transfer Entropy

Usage

te_disc(X, Y, p = 1, q = 1, log = "log2", normalize = FALSE)

Arguments

X	Integer vector, first time series.
Y	Integer vector, the second time series.
p	Integer, the lag parameter to use for the first vector (p = 1 by default).
q	Integer, the lag parameter to use for the first vector (q = 1 by default)..
log	String argument in the set ("log2", "loge","log10"), which indicates the log function to use. The log2 is used by default.
normalize	Logical argument for the option of normalizing the value of TE (transfer entropy) (FALSE by default). This normalization is done by deviding TE by H (X(t)| X(t-1), ..., X(t-p)), where H is the Shanon entropy.

Details

Computes the Transfer Entropy from the second time series to the first one.

References

\insertRef

schreiber2000NlinTS

Examples

library (NlinTS)
te = te_disc (c(3,2,4,4,3), c(1,4,4,3,3), 1, 1)
print (te)

Example output

Loading required package: Rcpp
[1] 0.5

NlinTS documentation built on Feb. 2, 2021, 9:07 a.m.