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Sufficient dimension reduction for censored predictors

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  • Diego Tomassi
  • Liliana Forzani
  • Efstathia Bura
  • Ruth Pfeiffer

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  • Diego Tomassi & Liliana Forzani & Efstathia Bura & Ruth Pfeiffer, 2017. "Sufficient dimension reduction for censored predictors," Biometrics, The International Biometric Society, vol. 73(1), pages 220-231, March.
    • Handle: RePEc:bla:biomet:v:73:y:2017:i:1:p:220-231
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    File URL: http://hdl.handle.net/10.1111/biom.12556
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    References listed on IDEAS

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    1. Cook, R. Dennis & Forzani, Liliana, 2009. "Likelihood-Based Sufficient Dimension Reduction," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 197-208.
    2. Margaret Pepe & Holly Janes & Gary Longton & Wendy Leisenring & Polly Newcomb, 2004. "Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic or Prognostic Marker," UW Biostatistics Working Paper Series 1035, Berkeley Electronic Press.
    3. Lee, Gyemin & Scott, Clayton, 2012. "EM algorithms for multivariate Gaussian mixture models with truncated and censored data," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2816-2829.
    4. Efstathia Bura & Liliana Forzani, 2015. "Sufficient Reductions in Regressions With Elliptically Contoured Inverse Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 420-434, March.
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    Cited by:

    1. Forzani, Liliana & Rodriguez, Daniela & Smucler, Ezequiel & Sued, Mariela, 2019. "Sufficient dimension reduction and prediction in regression: Asymptotic results," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 339-349.

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