id: 06054632
dt: j
an: 06054632
au: Hlaváčková-Schindler, K.
ti: Equivalence of Granger causality and transfer entropy: a generalization.
so: Appl. Math. Sci., Ruse 5, No. 73-76, 3637-3648 (2011).
py: 2011
pu: Hikari Ltd, Ruse
la: EN
cc: 
ut: generalized Gaussian probability distribution
ci: 
li: http://www.m-hikari.com/ams/ams-2011/ams-73-76-2011/index.html
ab: Summary: {\it L. Barnett, A.B. Barett} and {\it A.K. Seth} [Granger
    causality and transfer entropy are equivalent for Gaussian variables.
    Phys. Rev. Lett. 103, 23\,ff (2009)] proved that Granger causality and
    transfer entropy causality measure are equivalent for time series which
    have a Gaussian distribution. The Granger causality test is linear,
    while the transfer entropy is a nonlinear test. Many biological and
    physical mechanisms show to have non-Gaussian distributions. We
    investigate under which conditions on the density distributions of the
    data the equivalence of the two causality measures can be extended. In
    the complexity sense the “cheaper” linear Granger test can be
    applied for detection of causality in time series satisfying these
    conditions. These results have an impact on causality detection in
    common biological and physical time series.
rv: