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Even More Direct Calculation of the Variance of a Maximum Penalized-Likelihood Estimator

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  • Iain L. MacDonald
  • Brendon M. Lapham

Abstract

We discuss here two examples of estimation by numerical maximization of penalized likelihood. We show that, in these examples, it is simpler not to use the EM algorithm for computation of the estimates or their standard errors. We discuss also confidence and credibility intervals based on penalized likelihood and a chi-squared approximate distribution, and compare such intervals with intervals of Wald type.[Received July 2014. Revised September 2015.]

Suggested Citation

  • Iain L. MacDonald & Brendon M. Lapham, 2016. "Even More Direct Calculation of the Variance of a Maximum Penalized-Likelihood Estimator," The American Statistician, Taylor & Francis Journals, vol. 70(1), pages 114-118, February.
    • Handle: RePEc:taf:amstat:v:70:y:2016:i:1:p:114-118
    DOI: 10.1080/00031305.2015.1105151
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    References listed on IDEAS

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    1. Woojoo Lee & Yudi Pawitan, 2014. "Direct Calculation of the Variance of Maximum Penalized Likelihood Estimates via EM Algorithm," The American Statistician, Taylor & Francis Journals, vol. 68(2), pages 93-97, May.
    2. repec:dau:papers:123456789/1908 is not listed on IDEAS
    3. Sander Greenland, 2001. "Putting Background Information About Relative Risks into Conjugate Prior Distributions," Biometrics, The International Biometric Society, vol. 57(3), pages 663-670, September.
    4. Iain L. MacDonald, 2014. "Numerical Maximisation of Likelihood: A Neglected Alternative to EM?," International Statistical Review, International Statistical Institute, vol. 82(2), pages 296-308, August.
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    Cited by:

    1. Iain L. MacDonald, 2021. "Is EM really necessary here? Examples where it seems simpler not to use EM," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 629-647, December.

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