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Nonparametric maximum likelihood estimation for the multisample Wicksell corpuscle problem

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  • Kwun Chuen Gary Chan
  • Jing Qin

Abstract

We study nonparametric maximum likelihood estimation for the distribution of spherical radii using samples containing a mixture of one-dimensional, two-dimensional biased and three-dimensional unbiased observations. Since direct maximization of the likelihood function is intractable, we propose an expectation-maximization algorithm for implementing the estimator, which handles an indirect measurement problem and a sampling bias problem separately in the E- and M-steps, and circumvents the need to solve an Abel-type integral equation, which creates numerical instability in the one-sample problem. Extensions to ellipsoids are studied and connections to multiplicative censoring are discussed.

Suggested Citation

  • Kwun Chuen Gary Chan & Jing Qin, 2016. "Nonparametric maximum likelihood estimation for the multisample Wicksell corpuscle problem," Biometrika, Biometrika Trust, vol. 103(2), pages 273-286.
  • Handle: RePEc:oup:biomet:v:103:y:2016:i:2:p:273-286.
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    File URL: http://hdl.handle.net/10.1093/biomet/asw011
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    Cited by:

    1. Kwun Chuen Gary Chan, 2017. "Acceleration of Expectation-Maximization algorithm for length-biased right-censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 102-112, January.

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