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Computer Simulation Swindles, with Applications to Estimates of Location and Dispersion

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  • Gary Simon

Abstract

The notion of swindling to reduce the variances of simulation‐estimated quantities is discussed. A summary of variance‐reduction techniques is provided. Applications are given to the problems of appraising estimates of either location or dispersion in univariate samples, exploiting a normal‐over‐independent decomposition of the samples. Methods are also given for estimating the variance reductions achieved by swindles.

Suggested Citation

  • Gary Simon, 1976. "Computer Simulation Swindles, with Applications to Estimates of Location and Dispersion," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(3), pages 266-274, November.
    • Handle: RePEc:bla:jorssc:v:25:y:1976:i:3:p:266-274
    DOI: 10.2307/2347234
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    Cited by:

    1. Koenker, Roger & Machado, Jose A. F., 1998. "The Falstaff estimator," Economics Letters, Elsevier, vol. 61(1), pages 23-28, October.
    2. Giorgio Calzolari & F. Di Iorio & G. Fiorentini, 1999. "Indirect Estimation of Just-Identified Models with Control Variates," Econometrics Working Papers Archive quaderno46, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    3. Giorgio Calzolari & Francesca Di Iorio & Gabriele Fiorentini, 1998. "Control variates for variance reduction in indirect inference: Interest rate models in continuous time," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 100-112.
    4. Randal, John A., 2008. "A reinvestigation of robust scale estimation in finite samples," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 5014-5021, July.
    5. A. S. Hedayat & Guoqin Su, 2012. "Robustness of the Simultaneous Estimators of Location and Scale From Approximating a Histogram by a Normal Density Curve," The American Statistician, Taylor & Francis Journals, vol. 66(1), pages 25-33, February.

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