Information measures in records and their concomitants arising from Sarmanov family of bivariate distributions

Faculty Science Year: 2022
Type of Publication: ZU Hosted Pages:
Authors:
Islam Abdallah Heusseiny Metwally
Journal: Journal of Computational and Applied Mathematics ELSEVIER Volume: volume 408
Keywords : Information measures , records , their concomitants arising from    
Abstract:
One of the most pliable and robust extensions of the classical FGM family of bivariate distributions is the Sarmanov family, which was proposed and used by Sarmanov (1974) as a new model of hydrological processes, inter alia. Despite the salient and almost unique features of this family, it is never used in the literature. The distribution theory of concomitants of record values from this family is investigated. Furthermore, the joint distribution of concomitants of record values for this family is studied. Besides, some aspects of information measures, namely, the Shannon entropy, inaccuracy measure, extropy, cumulative entropy, and Fisher information number are studied. Illustrative examples are provided, where numerical studies lend further support to the theoretical results.
    
     
 
       

Author Related Publications

  • Islam Abdallah Heusseiny Metwally, "Information measures in records and their concomitants arising from Sarmanov family of bivariate distributions", Elsevier, 2022 More
  • Islam Abdallah Heusseiny Metwally, "Concomitants of Order Statistics and Record Values from Generalization of FGM Bivariate-Generalized Exponential Distribution", ATLANTIS PRESS, 2019 More
  • Islam Abdallah Heusseiny Metwally, "CONCOMITANTS OF ORDER STATISTICS AND RECORD VALUES FROM ITERATED FGM TYPE BIVARIATE-GENERALIZED EXPONENTIAL DIS- TRIBUTION", INSTITUTO NACIONAL DE ESTATISTICA, 2019 More
  • Islam Abdallah Heusseiny Metwally, "Bivariate Epanechnikov-Weibull distribution based on Sarmanov copula: properties, simulation, and uncertainty measures with applications", AIMS, 2025 More
  • Islam Abdallah Heusseiny Metwally, "The bivariate Weibull distribution based on the GFGM copula", AIMS, 2025 More

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