Abstract
We proposed “a new extension of three-parametric distribution” called the inverse power two-parameter weighted Lindley (IPWL) distribution capable of modeling a upside-down bathtub hazard rate function. This distribution is studied to get basic structural properties such as reliability measures, moments, inverse moments and its related measures. Simulation studies are done to present the performance and behavior of maximum likelihood estimates of the IPWL distribution parameters. Finally, we perform goodness of fit measures and test statistics using a real data set to show the performance of the new distribution.
Highlights
Lindley distribution is one way to describe the lifetime of a wide variety of fields, including biology, engineering and medicine
We proposed a new inverse two-parameter weighted Linley distribution which offers more flexibility with upside-down bathtub or unimodal hazard rate named the inverse power two-parameter weighted Lindley (IPWL) distribution
Inverse power two-parameter weighted Lindley distribution obtain a greater approximation between the empirical and the theoretical curves the proposed distribution was the one which best adjusted to the real data set
Summary
Lindley distribution is one way to describe the lifetime of a wide variety of fields, including biology, engineering and medicine. A few inverted statistical distributions such as inverted Rayleigh (IR), inverted Weibull (IW), and inverted Gamma (IG) are available to model such upside-down bathtub data These distributions have been extensively used in the various real-life applications. Alkarni [9] proposed the extended inverse two-parameter Lindley distribution as a statistical inverse model for upside-down bathtub survival data. We proposed a new inverse two-parameter weighted Linley distribution which offers more flexibility with upside-down bathtub or unimodal hazard rate named the inverse power two-parameter weighted Lindley (IPWL) distribution.
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