Evaluating Transfer Entropy for Normal and y-Order Normal Distributions

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00461261" target="_blank" >RIV/67985556:_____/16:00461261 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.9734/BJMCS/2016/27377" target="_blank" >http://dx.doi.org/10.9734/BJMCS/2016/27377</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.9734/BJMCS/2016/27377" target="_blank" >10.9734/BJMCS/2016/27377</a>

Result language
angličtina
Original language name
Evaluating Transfer Entropy for Normal and y-Order Normal Distributions
Original language description
Since its introduction, transfer entropy has become a popular information-theoretic tool for detecting causal inference between two discretized random processes. By means of statistical tools we evaluate the transfer entropy of stationary processes whose continuous probability distributions are known. We study transfer entropy of processes coming from the family of γ-order generalized normal distribution. Applying Kullback-Leibler divergence we provide explicit expressions of the transfer entropy for processes which are normal, as well as for processes from the class of γ-order normal distributions. The results achieved in the paper for continuous time can be applied also to the discrete time case, concretely to the time series whose underlying process distribution is from the discussed classes.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BC - Theory and management systems
OECD FORD branch
—

Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)