The inverse power Lindley distribution in the presence of left-censored data

Emílio A. Coelho-Barros, Josmar Mazucheli, Jorge A. Achcar, Kelly Vanessa Parede Barco and José Rafael Tovar Cuevas

Journal of Applied Statistics, 2018, vol. 45, issue 11, 2081-2094

Abstract: In this study, classical and Bayesian inference methods are introduced to analyze lifetime data sets in the presence of left censoring considering two generalizations of the Lindley distribution: a first generalization proposed by Ghitany et al. [Power Lindley distribution and associated inference, Comput. Statist. Data Anal. 64 (2013), pp. 20–33], denoted as a power Lindley distribution and a second generalization proposed by Sharma et al. [The inverse Lindley distribution: A stress–strength reliability model with application to head and neck cancer data, J. Ind. Prod. Eng. 32 (2015), pp. 162–173], denoted as an inverse Lindley distribution. In our approach, we have used a distribution obtained from these two generalizations denoted as an inverse power Lindley distribution. A numerical illustration is presented considering a dataset of thyroglobulin levels present in a group of individuals with differentiated cancer of thyroid.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:45:y:2018:i:11:p:2081-2094

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DOI: 10.1080/02664763.2017.1410525

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