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On computation of NPMLE for middle-censored data

Author

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  • Mangalam, Vasudevan
  • Nair, Gopalan M.
  • Zhao, Yun

Abstract

We consider data subjected to middle censoring where the variable of interest becomes unobservable when it falls within an interval of censorship. A necessary and sufficient condition is developed for the equivalence of self-consistent estimators and NPMLEs. Finding NPMLE by dividing the data into simpler subsets is considered.

Suggested Citation

  • Mangalam, Vasudevan & Nair, Gopalan M. & Zhao, Yun, 2008. "On computation of NPMLE for middle-censored data," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1452-1458, September.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:12:p:1452-1458
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    Cited by:

    1. P. G. Sankaran & S. Prasad, 2017. "An Additive Risks Regression Model For Middle-Censored Lifetime Data," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 459-479, September.
    2. Sankaran P. G. & Prasad S., 2017. "An Additive Risks Regression Model for Middle-Censored Lifetime Data," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 459-479, September.

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