A retrospective study on Lindley distribution

Tomy, Lishamol

doi:10.15406/bbij.2018.07.00205

Cited by 15 publications

(10 citation statements)

References 36 publications

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“…In recent years, there has been a great interest by many authors and researchers in the study of the Lindley distribution and its applications to model failure time data with increasing, decreasing, unimodal and bathtub shaped hazard rates. For details on Lindley distribution and its extension, the interested readers are referred to Lindley [ 17 ], Ghitany et al [ 12 ], Mazucheli and Achcar [ 21 ], Al-Mutairi et al [ 6 ], Cakmakyapan and Kadilar [ 7 ], Tomy [ 38 ], and references therein.…”

Section: Introductionmentioning

confidence: 99%

Ratio of Two Independent Lindley Random Variables

et al. 2022

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The distribution of the ratio of two independently distributed Lindley random variables $$X$$ X and $$Y$$ Y , with different parameters, is derived. The associated distributional properties are provided. Furthermore, the proposed ratio distribution is fitted to two applications data (COVID-19 and Bladder Cancer Data), and compared it with some well-known right-skewed variations of Lindley distribution, namely; Lindley distribution, new generalized Lindley distribution, new quasi Lindley distribution and a three parameter Lindley distribution. The numerical result of the study reveals that the proposed distribution of two independent Lindley random variables fits better to the above said data sets than the compared distribution.

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Section: Introductionmentioning

confidence: 99%

Ratio of Two Independent Lindley Random Variables

et al. 2022

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“…Many generalizations of the Lindley distribution were developed. We redirect the readers to Tomy 3 and Chesneau 4 to get a better understanding of the different generalizations and applications of the Lindley distribution.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of various estimation methods for modified Lindley distribution

Veena¹,

Tomy²

2022

BBIJ

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The purpose of this study is to examine the finite sample aspects of estimates of the parameters of the weighted Lindley distribution derived by four estimation methods: maximum likelihood, method of moments, ordinary least squares, and weighted least squares, using Monte Carlo simulations. As a comparison criterion, bias and mean-squared error are used. In both small and large samples, the Cramer-von Mises approach is found to be very competing with the maximum likelihood method. To substantiate the conclusion, a statistical analysis of a real data set related to weather is performed.

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“…Providing flexible and accurate distributions is sought in a variety of contexts, including public health, biomedical studies, and reliability (for a fuller discussion, see [1]). Lindley [2] pioneered the one-parameter Lindley distribution, to which several extensions have been developed [3]. Abouammoh and Kayid [4] developed a general form for Lindeybased extended models.…”

Section: Introductionmentioning

confidence: 99%

An Extended log-Lindley-G Family: Properties and Experiments in Repairable Data

2021

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In this article, two new families of distributions are proposed: the generalized log-Lindley-G (GLL-G) and its counterpart, the GLL*-G. These families can be justified by their relation to the log-Lindley model, an important assumption for describing social and economic phenomena. Specific GLL models are introduced and studied. We show that the GLL density is rewritten as a two-member linear combination of the exponentiated G-densities and that, consequently, many of its mathematical properties arise directly, such as moment-based expressions. A maximum likelihood estimation procedure for the GLL parameters is provided and the behavior of the resulting estimates is evaluated by Monte Carlo experiments. An application to repairable data is made. The results argue for the use of the exponential law as the basis for the GLL-G family.

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A retrospective study on Lindley distribution

Cited by 15 publications

References 36 publications

Ratio of Two Independent Lindley Random Variables

Ratio of Two Independent Lindley Random Variables

A comparative study of various estimation methods for modified Lindley distribution

An Extended log-Lindley-G Family: Properties and Experiments in Repairable Data

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