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Notes on Pearson residuals and weighted likelihood estimating equations

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  • Agostinelli, Claudio

Abstract

In these notes we show that the Pearson residuals (PR) [Lindsay, B.G., 1994. Efficiency versus robustness: the case for minimum Hellinger distance and related methods. Ann. Statist. 22, 1018-1114.] have a natural asymptotic lower bound under the gross error model which can be used in the problem of choosing a root when multiple roots are present in the weighted likelihood estimating equations. Further, we show through an example how the minimum of the PR plays an important role in the robust estimation approach based on weighted likelihood.

Suggested Citation

  • Agostinelli, Claudio, 2006. "Notes on Pearson residuals and weighted likelihood estimating equations," Statistics & Probability Letters, Elsevier, vol. 76(17), pages 1930-1934, November.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:17:p:1930-1934
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    References listed on IDEAS

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    1. Park, Chanseok & Basu, Ayanendranath & G. Lindsay, Bruce, 2002. "The residual adjustment function and weighted likelihood: a graphical interpretation of robustness of minimum disparity estimators," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 21-33, March.
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    Cited by:

    1. Giovanni Saraceno & Claudio Agostinelli & Luca Greco, 2021. "Robust estimation for multivariate wrapped models," METRON, Springer;Sapienza Università di Roma, vol. 79(2), pages 225-240, August.
    2. Luca Greco & Antonio Lucadamo & Claudio Agostinelli, 2021. "Weighted likelihood latent class linear regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 711-746, June.
    3. Agostinelli, Claudio, 2007. "Robust estimation for circular data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5867-5875, August.
    4. Claudio Agostinelli & Luca Greco, 2019. "Weighted likelihood estimation of multivariate location and scatter," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 756-784, September.

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