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Statistical Inference, Learning and Models in Big Data

Author

Listed:
  • Beate Franke
  • Jean-FRANçois Plante
  • Ribana Roscher
  • En-shiun Annie Lee
  • Cathal Smyth
  • Armin Hatefi
  • Fuqi Chen
  • Einat Gil
  • Alexander Schwing
  • Alessandro Selvitella
  • Michael M. Hoffman
  • Roger Grosse
  • Dieter Hendricks
  • Nancy Reid

Abstract

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Suggested Citation

  • Beate Franke & Jean-FRANçois Plante & Ribana Roscher & En-shiun Annie Lee & Cathal Smyth & Armin Hatefi & Fuqi Chen & Einat Gil & Alexander Schwing & Alessandro Selvitella & Michael M. Hoffman & Roger, 2016. "Statistical Inference, Learning and Models in Big Data," International Statistical Review, International Statistical Institute, vol. 84(3), pages 371-389, December.
    • Handle: RePEc:bla:istatr:v:84:y:2016:i:3:p:371-389
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    File URL: http://hdl.handle.net/10.1111/insr.12176
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    References listed on IDEAS

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    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Wei Biao Wu, 2003. "Nonparametric estimation of large covariance matrices of longitudinal data," Biometrika, Biometrika Trust, vol. 90(4), pages 831-844, December.
    3. Declan Butler, 2013. "When Google got flu wrong," Nature, Nature, vol. 494(7436), pages 155-156, February.
    4. Ariel Kleiner & Ameet Talwalkar & Purnamrita Sarkar & Michael I. Jordan, 2014. "A scalable bootstrap for massive data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(4), pages 795-816, September.
    5. Siu-Ming Tam & Frederic Clarke, 2015. "Big Data, Official Statistics and Some Initiatives by the Australian Bureau of Statistics," International Statistical Review, International Statistical Institute, vol. 83(3), pages 436-448, December.
    6. P. Nguyen & P. E. Brown & J. Stafford, 2012. "Mapping Cancer Risk in Southwestern Ontario with Changing Census Boundaries," Biometrics, The International Biometric Society, vol. 68(4), pages 1228-1237, December.
    7. Mark Girolami & Ben Calderhead, 2011. "Riemann manifold Langevin and Hamiltonian Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(2), pages 123-214, March.
    8. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
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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. Espasa, Antoni & Carlomagno Real, Guillermo, 2023. "Tall big data time series of high frequency: stylized facts and econometric modelling," DES - Working Papers. Statistics and Econometrics. WS 37746, Universidad Carlos III de Madrid. Departamento de Estadística.

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