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Modelling time‐varying mobility flows using function‐on‐function regression: Analysis of a bike sharing system in the city of Milan

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  • Agostino Torti
  • Alessia Pini
  • Simone Vantini

Abstract

In today's world, bike sharing systems are becoming increasingly common in all main cities around the world. To understand the spatiotemporal patterns of how people move by bike through the city of Milan, we apply functional data analysis to study the flows of a bike sharing mobility network. We introduce a complete pipeline to properly analyse and model functional data through a concurrent functional‐on‐functional model taking into account the effects of weather conditions and calendar on the bike flows. In the end, we develop an interactive interface to explore the results of the analyses.

Suggested Citation

  • Agostino Torti & Alessia Pini & Simone Vantini, 2021. "Modelling time‐varying mobility flows using function‐on‐function regression: Analysis of a bike sharing system in the city of Milan," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 226-247, January.
    • Handle: RePEc:bla:jorssc:v:70:y:2021:i:1:p:226-247
    DOI: 10.1111/rssc.12456
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    References listed on IDEAS

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    Cited by:

    1. Diquigiovanni, Jacopo & Fontana, Matteo & Vantini, Simone, 2022. "Conformal prediction bands for multivariate functional data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    2. Agostino Torti & Marika Arena & Giovanni Azzone & Piercesare Secchi & Simone Vantini, 2022. "Bridge closure in the road network of Lombardy: a spatio-temporal analysis of the socio-economic impacts," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 901-923, October.

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