About: The statistical physics of discovering exogenous and endogenous factors in a chain of events

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	The statistical physics of discovering exogenous and endogenous factors in a chain of events
Creator	Koyama, Shinsuke Shinomoto, Shigeru
source	ArXiv
abstract	Event occurrence is not only subject to the environmental changes, but is also facilitated by the events that have occurred in a system. Here, we develop a method for estimating such extrinsic and intrinsic factors from a single series of event-occurrence times. The analysis is performed using a model that combines the inhomogeneous Poisson process and the Hawkes process, which represent exogenous fluctuations and endogenous chain-reaction mechanisms, respectively. The model is fit to a given dataset by minimizing the free energy, for which statistical physics and a path-integral method are utilized. Because the process of event occurrence is stochastic, parameter estimation is inevitably accompanied by errors, and it can ultimately occur that exogenous and endogenous factors cannot be captured even with the best estimator. We obtained four regimes categorized according to whether respective factors are detected. By applying the analytical method to real time series of debate in a social-networking service, we have observed that the estimated exogenous and endogenous factors are close to the first comments and the follow-up comments, respectively. This method is general and applicable to a variety of data, and we have provided an application program, by which anyone can analyze any series of event times.
has issue date	2020-03-02(xsd:dateTime)
has license	arxiv
sha1sum (hex)	102ab41f432f6fd482d16724b0416a326de9a218
resource representing a document's title	The statistical physics of discovering exogenous and endogenous factors in a chain of events
resource representing a document's body	covid:102ab41f432f6fd482d16724b0416a326de9a218#body_text
is schema:about of	named entity 'inhomogeneous Poisson process' named entity 'estimator' named entity 'application program' named entity 'Laplace transform' named entity 'exogenous' »more»

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