Entropy Estimation From Ranked Set Samples With Application to Test of Fit

• EHSAN ZAMANZADE ^[1] ; M. MAHDIZADEH ^[2]
  1. [1] University of Isfahan

     University of Isfahan

     Irán

     
  2. [2] Hakim Sabzevari University Department of Statistics
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 40, Nº. 2, 2017, págs. 223-241
• Idioma: inglés
• DOI: 10.15446/rce.v40n2.58944
• Títulos paralelos:
  • Estimación de entropía de muestras de rango ordenado con aplicación a pruebas de ajuste
• Enlaces
  • Texto completo
• Resumen
  • español

    Este artículo trata sobre la estimación de entropía usando muestras de rango ordenado (RSS). Algunos estimadores se desarrollan con base en distribuciones empíricas y si estimación no paramétrica de máxima verosimilitud. Los estimadores de entropía sugeridos tienen menor raíz del error de cuadrados medios que otros reportados en literatura. Los estimadores propuestos son usados para construir pruebas de bondad de ajuste para distribuciones inversas Gaussianas.

  • English

    This article deals with entropy estimation using ranked set sampling (RSS). Some estimators are developed based on the empirical distribution function and its nonparametric maximum likelihood competitor. The suggested entropy estimators have smaller root mean squared errors than the other entropy estimators in the literature. The proposed estimators are then used to construct goodness of fit tests for inverse Gaussian distribution.

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