Propagation graph estimation from individuals' time series of observed states


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Title:	Propagation graph estimation from individuals' time series of observed states
Authors:	Hayashi, Tatsuya Browse this author →KAKEN DB
Authors:	Nakamura, Atsuyoshi Browse this author →KAKEN DB
Issue Date:	12-Apr-2022
Publisher:	Nature Portfolio
Journal Title:	Scientific reports
Volume:	12
Issue:	1
Start Page:	6078
Publisher DOI:	10.1038/s41598-022-10031-3
Abstract:	Various things propagate through the medium of individuals. Some individuals follow the others and take the states similar to their states a small number of time steps later. In this paper, we study the problem of estimating the state propagation order of individuals from the real-valued state sequences of all the individuals.We propose a method of constructing a state propagation graph from individuals' time series of observed states. The propagation order estimated by our proposed method is demonstrated to be significantly more accurate than that by a baseline method (optimal constant delay model) for our synthetic datasets, and also to be consistent with visually recognizable propagation orders for the dataset of Japanese stock price time series and biological cell firing state sequences.
Type:	article
URI:	http://hdl.handle.net/2115/85549
Appears in Collections:	情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

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