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Strong consistency of MLE for finite uniform mixtures when the scale parameters are exponentially small

Author

Listed:
  • Kentaro Tanaka
  • Akimichi Takemura

Abstract

No abstract is available for this item.

Suggested Citation

  • Kentaro Tanaka & Akimichi Takemura, 2005. "Strong consistency of MLE for finite uniform mixtures when the scale parameters are exponentially small," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(1), pages 1-19, March.
    • Handle: RePEc:spr:aistmt:v:57:y:2005:i:1:p:1-19
    DOI: 10.1007/BF02506875
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    Citations

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    Cited by:

    1. Mingxing He & Jiahua Chen, 2022. "Strong consistency of the MLE under two-parameter Gamma mixture models with a structural scale parameter," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 125-154, March.
    2. Mingxing He & Jiahua Chen, 2022. "Consistency of the MLE under a two-parameter Gamma mixture model with a structural shape parameter," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 951-975, November.
    3. Kentaro Tanaka, 2009. "Strong Consistency of the Maximum Likelihood Estimator for Finite Mixtures of Location–Scale Distributions When Penalty is Imposed on the Ratios of the Scale Parameters," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(1), pages 171-184, March.

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