Extropy Based on Concomitants of Order Statistics in Farlie-Gumbel-Morgenstern Family for Random Variables Representing Past Life

Muhammed Rasheed Irshad; Krishnakumar Archana; Amer Ibrahim Al-Omari; Radhakumari Maya; Ghadah Alomani

doi:10.3390/axioms12080792

Axioms (Aug 2023)

Extropy Based on Concomitants of Order Statistics in Farlie-Gumbel-Morgenstern Family for Random Variables Representing Past Life

Muhammed Rasheed Irshad,
Krishnakumar Archana,
Amer Ibrahim Al-Omari,
Radhakumari Maya,
Ghadah Alomani

Affiliations

Muhammed Rasheed Irshad: Department of Statistics, Cochin University of Science and Technology, Cochin 682 022, Kerala, India
Krishnakumar Archana: Department of Statistics, Cochin University of Science and Technology, Cochin 682 022, Kerala, India
Amer Ibrahim Al-Omari: Department of Mathematics, Faculty of Science, Al al-Bayt University, Mafraq 251113, Jordan
Radhakumari Maya: Department of Statistics, University College, Trivandrum 695 034, Kerala, India
Ghadah Alomani: Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia

DOI: https://doi.org/10.3390/axioms12080792
Journal volume & issue: Vol. 12, no. 8
p. 792

Abstract

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In this paper, we refined the concept of past extropy measure for concomitants of order statistics from Farlie-Gumbel-Morgenstern family. In addition, cumulative past extropy measure and dynamic cumulative past extropy measure for concomitant of rth order statistic are also conferred and their properties are studied. The problem of estimating the cumulative past extropy is investigated using empirical technique. The validity of the proposed estimator has been emphasized using simulation study.

Published in Axioms

ISSN: 2075-1680 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science: Mathematics
Website: http://www.mdpi.com/journal/axioms

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