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Abstract
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This article introduces a novel class of skew-logistic distribution, providing flexibility
to fit data with up to three modes. Various important properties of this new distribution
are thoroughly examined, including its moment generating function, moments, entropy,
and characterizations. Considering the location and scale parameters, a model extension
and its parameter estimation technique are included. The study also includes a simulation
study using the Metropolis–Hastings algorithm to observe the behavior of the estimated
parameters. Furthermore, the adaptability and utility of the new model are assessed
using three real-life datasets. Finally, a likelihood ratio test is applied to distinguish the
introduced model from some other simpler models.
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