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Journeys in big data statistics

Author

Listed:
  • Dryden, Ian L.
  • Hodge, David J.

Abstract

The realm of big data is a very wide and varied one. We discuss old, new, small and big data, with some of the important challenges including dealing with highly-structured and object-oriented data. In many applications the objective is to discern patterns and learn from large datasets of historical data. We shall discuss such issues in some transportation network applications in non-academic settings, which are naturally applicable to other situations. Vital aspects include dealing with logistics, coding and choosing appropriate statistical methodology, and we provide a summary and checklist for wider implementation.

Suggested Citation

  • Dryden, Ian L. & Hodge, David J., 2018. "Journeys in big data statistics," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 121-125.
    • Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:121-125
    DOI: 10.1016/j.spl.2018.02.013
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    Cited by:

    1. Reid, Nancy, 2018. "Statistical science in the world of big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 42-45.
    2. Olhede, Sofia C. & Wolfe, Patrick J., 2018. "The future of statistics and data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 46-50.
    3. Pedro Galeano & Daniel Peña, 2019. "Data science, big data and statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 289-329, June.

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