Abstract
This paper presents a new four-parameter lifetime model by generalizing the Inverse Weibull (IW) distribution using Transmuted Kumaraswamy family of distributions. The proposed model explains the high probability at the tail effectively. The induction of additional parameters enhance the potentiality of the IW distribution and make it a pliant model that provides a vast range of existing distributions as special cases. Several probabilistic properties of the proposed model including moments, probability weighted moments, moment generating function, quantile function, reliability measures, and order statistics are discussed. The maximum likelihood (ML) procedure is adopted for the estimation of model parameters. The efficiency of ML estimates is to testify through simulation study. Four datasets from the field of reliability science are used to expound the competence of the proposed model.
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