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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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    1. Usset, Joseph & Staicu, Ana-Maria & Maity, Arnab, 2016. "Interaction models for functional regression," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 317-329.
    2. Li, Yehua & Wang, Naisyin & Carroll, Raymond J., 2010. "Generalized Functional Linear Models With Semiparametric Single-Index Interactions," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 621-633.
    3. Chiou, Jeng-Min & Muller, Hans-Georg, 2007. "Diagnostics for functional regression via residual processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4849-4863, June.
    4. Canale, Antonio & Vantini, Simone, 2016. "Constrained functional time series: Applications to the Italian gas market," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1340-1351.
    5. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    6. A. Pini & S. Vantini, 2017. "Interval-wise testing for functional data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 407-424, April.
    7. Xiaolu Zhou, 2015. "Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    8. Saberi, Meead & Ghamami, Mehrnaz & Gu, Yi & Shojaei, Mohammad Hossein (Sam) & Fishman, Elliot, 2018. "Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London," Journal of Transport Geography, Elsevier, vol. 66(C), pages 154-166.
    9. Konrad Abramowicz & Charlotte K. Häger & Alessia Pini & Lina Schelin & Sara Sjöstedt de Luna & Simone Vantini, 2018. "Nonparametric inference for functional‐on‐scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(4), pages 1036-1061, December.
    10. J. Goldsmith & S. Greven & C. Crainiceanu, 2013. "Corrected Confidence Bands for Functional Data Using Principal Components," Biometrics, The International Biometric Society, vol. 69(1), pages 41-51, March.
    11. Freedman, David & Lane, David, 1983. "A Nonstochastic Interpretation of Reported Significance Levels," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 292-298, October.
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    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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