Description Usage Arguments Details References Examples
Continuous Transfer Entropy
1 |
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). |
k |
Integer argument, the number of neighbors. |
normalize |
Logical argument for the option of normalizing value of TE (transfer entropy) (FALSE by default). This normalization is different from the discrete case, because, here the term H (X(t)| X(t-1), ..., X(t-p)) may be negative. Consequently, we use another technique, we divide TE by H0 - H (X(t)| X(t-1), ..., X(t-p), Yt-1), ..., Y(t-q)), where H0 is the max entropy (of uniform distribution). |
Computes the continuous Transfer Entropy from the second time series to the first one using the Kraskov estimation
kraskov2004estimatingNlinTS
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Loading required package: Rcpp
Loading required package: timeDate
[1] 1.646321
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