6 research outputs found
Hawkes process as a model of social interactions: a view on video dynamics
We study by computer simulation the "Hawkes process" that was proposed in a
recent paper by Crane and Sornette (Proc. Nat. Acad. Sci. USA 105, 15649
(2008)) as a plausible model for the dynamics of YouTube video viewing numbers.
We test the claims made there that robust identification is possible for
classes of dynamic response following activity bursts. Our simulated timeseries
for the Hawkes process indeed fall into the different categories predicted by
Crane and Sornette. However the Hawkes process gives a much narrower spread of
decay exponents than the YouTube data, suggesting limits to the universality of
the Hawkes-based analysis.Comment: Added errors to parameter estimates and further description. IOP
style, 13 pages, 5 figure
The Visibility Graph: a new method for estimating the Hurst exponent of fractional Brownian motion
Fractional Brownian motion (fBm) has been used as a theoretical framework to
study real time series appearing in diverse scientific fields. Because its
intrinsic non-stationarity and long range dependence, its characterization via
the Hurst parameter H requires sophisticated techniques that often yield
ambiguous results. In this work we show that fBm series map into a scale free
visibility graph whose degree distribution is a function of H. Concretely, it
is shown that the exponent of the power law degree distribution depends
linearly on H. This also applies to fractional Gaussian noises (fGn) and
generic f^(-b) noises. Taking advantage of these facts, we propose a brand new
methodology to quantify long range dependence in these series. Its reliability
is confirmed with extensive numerical simulations and analytical developments.
Finally, we illustrate this method quantifying the persistent behavior of human
gait dynamics.Comment: 5 pages, submitted for publicatio