On some inferential aspects of length biased log-logistic model

Ranjita Pandey, Pulkit Srivastava () and Neera Kumari
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Ranjita Pandey: University of Delhi
Pulkit Srivastava: University of Delhi
Neera Kumari: BFIT

International Journal of System Assurance Engineering and Management, 2021, vol. 12, issue 1, No 16, 154-163

Abstract: Abstract In this paper, we study a weighted distribution which is known to provide adjustment to the base distribution by ascertaining the probability of the actual occurrence of events vis-a-vis records and observations. Log-logistic distribution is a widely used time to event model with heavy tails. We introduce a two parameter length biased log-logistic distribution which is a special case of weighted distribution. Comprehensive description of its various mathematical properties is given. Moment generating function, order statistics and entropy aspects are examined. Stochastic orderings and likelihood ratio are also discussed. The proposed distribution is shown to have a promising potential as a better reliability model. Its advantage over five other popular time to event models is demonstrated through empirical fitting of a classical data set.

Keywords: Length biased model; Log logistic distribution; Entropy; Order statistics; Stochastic ordering (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s13198-020-01027-1

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