Comparative regression analysis to degree distributions of visibility graph

doi:10.3969/j.issn.1000-5641.2017.02.010

Abstract

Abstract:

Visibility graph has provided much insight to study the dynamics of time series from the perspective complex network. We construct visibility graphs for time series from both auto-regressive stochastic and fractional Brownian motions. Our results suggest that degree distributions of the resulted complex networks of auto-regressive processes are characterized by exponential forms, while that of fractional Brownian motions obey power-law forms. Our conclusions hold for both the traditional visibility graph and its variant horizontal visibility graph.

Key words: visibility graph, autoregressive stochastic process, fractional Brownian motion, goodness of fit

CLC Number:

O415

ZHANG Rong, ZOU Yong. Comparative regression analysis to degree distributions of visibility graph[J]. Journal of East China Normal University(Natural Sc, 2017, 2017(2): 75-80.

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