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Minimum Variance Quadratic Unbiased Estimators as a Tool to Identify Compound Normal Distributions

Author

Listed:
  • Rolle, J.D.

Abstract

We drive the minimum variance quadratic unbiased estimator (MIVQUE) of the variance of the components of a random vector having a compound normal distribution (CND). We show that the MIVQUE converges in probability to a random variable whose distribution is essentially the mixing distribution characterising the CND.

Suggested Citation

  • Rolle, J.D., 1996. "Minimum Variance Quadratic Unbiased Estimators as a Tool to Identify Compound Normal Distributions," Papers 96.25, Ecole des Hautes Etudes Commerciales, Universite de Geneve-.
    • Handle: RePEc:fth:ehecge:96.25
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    More about this item

    Keywords

    LINEAR MODELS; REGRESSION ANALYSIS;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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