The Rayleigh–Lindley model: properties and applications

Yolanda M. Gómez, Diego I. Gallardo, Yuri Iriarte and Heleno Bolfarine

Journal of Applied Statistics, 2019, vol. 46, issue 1, 141-163

Abstract: In this paper, the Rayleigh–Lindley (RL) distribution is introduced, obtained by compounding the Rayleigh and Lindley discrete distributions, where the compounding procedure follows an approach similar to the one previously studied by Adamidis and Loukas in some other contexts. The resulting distribution is a two-parameter model, which is competitive with other parsimonious models such as the gamma and Weibull distributions. We study some properties of this new model such as the moments and the mean residual life. The estimation was approached via EM algorithm. The behavior of these estimators was studied in finite samples through a simulation study. Finally, we report two real data illustrations in order to show the performance of the proposed model versus other common two-parameter models in the literature. The main conclusion is that the model proposed can be a valid alternative to other competing models well established in the literature.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:46:y:2019:i:1:p:141-163

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DOI: 10.1080/02664763.2018.1458825

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