Abstract

In this work, we study the two-parameter Odd Lindley Weibull lifetime model. This distribution is motivated by the wide use of the Weibull model in many applied areas and also for the fact that this new generalization provides more flexibility to analyze real data. The Odd Lindley Weibull density function can be written as a linear combination of the exponentiated Weibull densities. We derive explicit expressions for the ordinary and incomplete moments, moments of the (reversed) residual life, generating functions and order statistics. We discuss the maximum likelihood estimation of the model parameters. We assess the performance of the maximum likelihood estimators in terms of biases, variances, mean squared of errors by means of a simulation study. The usefulness of the new model is illustrated by means of two real data sets. The new model provides consistently better fits than other competitive models for these data sets. The Odd Lindley Weibull lifetime model is much better than \ Weibull, exponential Weibull, Kumaraswamy Weibull, beta Weibull, and the three parameters odd lindly Weibull with three parameters models so the Odd Lindley Weibull model is a good alternative to these models in modeling glass fibres data as well as the Odd Lindley Weibull model is much better than the Weibull, Lindley Weibull transmuted complementary Weibull geometric and beta Weibull models so it is a good alternative to these models in modeling time-to-failure data.

Highlights

  • IntroductionThe goal of this paper is to introduce a new two parameter alternative to the Weibull, beta Weibull, Lindley Weibull, exponential Weibull, Kumaraswamy Weibull, transmuted complementary Weibull geometric and the tree parameters Odd lindly Weibull (OLW) models that overcomes these mentioned drawbacks

  • The goal of this paper is to introduce a new two parameter alternative to the Weibull, beta Weibull, Lindley Weibull, exponential Weibull, Kumaraswamy Weibull, transmuted complementary Weibull geometric and the tree parameters Odd lindly Weibull (OLW) models that overcomes these mentioned drawbacks.The probability density function (PDF) and CDF of the Weibull (W) distribution are given by g(x, β) = βxβ−1 exp ( − β x ) (1) and G(x, β) −

  • The usefulness of the new model is illustrated by means of two real data sets

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Summary

Introduction

The goal of this paper is to introduce a new two parameter alternative to the Weibull, beta Weibull, Lindley Weibull, exponential Weibull, Kumaraswamy Weibull, transmuted complementary Weibull geometric and the tree parameters Odd lindly Weibull (OLW) models that overcomes these mentioned drawbacks. It can be viewed as a suitable model for fitting the unimodal and left skewed data. The OLW lifetime model is much better than Weibull, exponential Weibull, Kumaraswamy Weibull, beta Weibull, and the three parameters Odd lindly Weibull with three parameters models so the OLW lifetime model is a good alternative to these models in modeling glass fibres data as well as the OLW lifetime model is much better than the Weibull, Lindley Weibull transmuted complementary Weibull geometric and beta Weibull models so the OLW lifetime model is a good alternative to these models in modeling time-to-failure data

Quantile Functions
Order Statistics and Their Moments
Moment of Residual and Reversed Residual Lifes
Maximum Likelihood Method
Simulation Studies
Real Data Analysis
Discussion

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