Visibility Graph Based Time Series Analysis
نویسندگان
چکیده
منابع مشابه
Visibility Graph Based Time Series Analysis
Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a...
متن کاملTime series irreversibility: a visibility graph approach
We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) b...
متن کاملFrom time series to complex networks: the visibility graph.
In this work we present a simple and fast computational method, the visibility algorithm, that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that po...
متن کاملStatistical validation of financial time series via visibility graph
Matteo Serafino, Andrea Gabrielli, 3, 4 Guido Caldarelli, 2, 4, 5 and Giulio Cimini 2, ∗ Dipartimento di Fisica, Università “Sapienza”, Piazzale Aldo Moro 5, 00185 Rome Italy Istituto dei Sistemi Complessi (ISC)-CNR UoS Università “Sapienza”, Piazzale Aldo Moro 5, 00185 Rome Italy IMT School for Advanced Studies, Piazza S.Francesco 19, 55100 Lucca Italy London Institute for Mathematical Science...
متن کاملDiscriminating Chaotic Time Series with Visibility Graph Eigenvalues
Time series can be transformed into graphs called horizontal visibility graphs (HVGs) in order to gain useful insights. Here, the maximum eigenvalue of the adjacency matrix associated to the HVG derived from several time series is calculated. The maximum eigenvalue methodology is able to discriminate between chaos and randomness and is suitable for short time series, hence for experimental resu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2015
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0143015