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Robust and Efficient Parametric Estimation for Censored Survival Data

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Abstract

We fit parametric models to survival data in the case of censoring and (outlier) contamination. To do so, we adapt the robust density power divergence methodology of Basu, Harris, Hjort, and Jones (Biometrika, 85, 549–559, 1998) to the case of censored survival data. Asymptotic properties, simulation performance and application to data are provided.

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Authors and Affiliations

  1. Skytech Solutions Pvt Ltd, BIPPL Bldg A, Salt Lake Electronics Complex, Kolkata, 700 091, India

    Srabashi Basu

  2. Applied Statistics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, India

    Ayanendranath Basu

  3. Department of Statistics, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK

    M. C. Jones

Authors
  1. Srabashi Basu
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  2. Ayanendranath Basu
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  3. M. C. Jones
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Corresponding author

Correspondence to M. C. Jones.

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Basu, S., Basu, A. & Jones, M.C. Robust and Efficient Parametric Estimation for Censored Survival Data. Ann Inst Stat Math 58, 341–355 (2006). https://doi.org/10.1007/s10463-005-0004-x

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  • DOI: https://doi.org/10.1007/s10463-005-0004-x

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