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Maximum integrated likelihood estimator of the interest parameter when the nuisance parameter is location or scale

Author

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  • Zaigraev, A.
  • Podraza-Karakulska, A.

Abstract

The problem of estimation of an interest parameter in the presence of a nuisance parameter, which is either location or scale, is studied. Two estimators are considered: the usual maximum likelihood estimator and the estimator based on maximization of the integrated likelihood function. The estimators are compared, asymptotically, with respect to the bias and with respect to the mean squared error. The examples are given.

Suggested Citation

  • Zaigraev, A. & Podraza-Karakulska, A., 2014. "Maximum integrated likelihood estimator of the interest parameter when the nuisance parameter is location or scale," Statistics & Probability Letters, Elsevier, vol. 88(C), pages 99-106.
    • Handle: RePEc:eee:stapro:v:88:y:2014:i:c:p:99-106
    DOI: 10.1016/j.spl.2014.01.024
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    References listed on IDEAS

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    1. Zaigraev, A. & Podraza-Karakulska, A., 2008. "On estimation of the shape parameter of the gamma distribution," Statistics & Probability Letters, Elsevier, vol. 78(3), pages 286-295, February.
    2. T. Yanagimoto, 1988. "The conditional maximum likelihood estimator of the shape parameter in the gamma distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 35(1), pages 161-175, December.
    3. T. A. Severini, 2010. "Likelihood ratio statistics based on an integrated likelihood," Biometrika, Biometrika Trust, vol. 97(2), pages 481-496.
    4. Thomas A. Severini, 2007. "Integrated likelihood functions for non-Bayesian inference," Biometrika, Biometrika Trust, vol. 94(3), pages 529-542.
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    Cited by:

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