# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "mFLICA" in publications use:' type: software license: GPL-3.0-only title: 'mFLICA: Leadership-Inference Framework for Multivariate Time Series' version: 0.1.6 identifiers: - type: doi value: 10.32614/CRAN.package.mFLICA abstract: A leadership-inference framework for multivariate time series. The framework for multiple-faction-leadership inference from coordinated activities or 'mFLICA' uses a notion of a leader as an individual who initiates collective patterns that everyone in a group follows. Given a set of time series of individual activities, our goal is to identify periods of coordinated activity, find factions of coordination if more than one exist, as well as identify leaders of each faction. For each time step, the framework infers following relations between individual time series, then identifying a leader of each faction whom many individuals follow but it follows no one. A faction is defined as a group of individuals that everyone follows the same leader. 'mFLICA' reports following relations, leaders of factions, and members of each faction for each time step. Please see Chainarong Amornbunchornvej and Tanya Berger-Wolf (2018) for methodology and Chainarong Amornbunchornvej (2021) for software when referring to this package in publications. authors: - family-names: Amornbunchornvej given-names: Chainarong email: grandca@gmail.com orcid: https://orcid.org/0000-0003-3131-0370 preferred-citation: type: proceedings title: Framework for Inferring Leadership Dynamics of Complex Movement from Time Series. authors: - family-names: Amornbunchornvej given-names: Chainarong email: grandca@gmail.com orcid: https://orcid.org/0000-0003-3131-0370 - family-names: Berger-Wolf given-names: Tanya Y. collection-title: Proceedings of the 2018 SIAM International Conference on Data Mining (SDM) collection-type: proceedings year: '2018' url: https://doi.org/10.1137/1.9781611975321.62 publisher: name: Society for Industrial and Applied Mathematics (SIAM) start: 549-557 conference: name: Proceedings of the 2018 SIAM International Conference on Data Mining (SDM) repository: https://darkeyes.r-universe.dev repository-code: https://github.com/DarkEyes/mFLICA commit: 5ddc49112e44084207ea8346414d5f8c6eb745f5 url: https://github.com/DarkEyes/mFLICA contact: - family-names: Amornbunchornvej given-names: Chainarong email: grandca@gmail.com orcid: https://orcid.org/0000-0003-3131-0370