Extended Inverse Lindley distribution

2021 ◽  
Author(s):  
V. D. Maharani ◽  
D. Lestari ◽  
S. Devila
Keyword(s):  
Lindley Distribution ◽  
Inverse Lindley Distribution ◽  
Extended Inverse Lindley Distribution

scholarly journals A Lomax-inverse Lindley Distribution: Model, Properties and Applications to Lifetime Data

2019 ◽  
pp. 1-28
Author(s):  
Terna Godfrey Ieren ◽  
Peter Oluwaseun Koleoso ◽  
Adana’a Felix Chama ◽  
Innocent Boyle Eraikhuemen ◽  
Nasiru Yakubu
Keyword(s):  
Likelihood Estimation ◽  
Quantile Function ◽  
Distribution Model ◽  
Lindley Distribution ◽  
Limiting Behavior ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
Inverse Lindley Distribution ◽  
New Distribution ◽  
Better Than

This article proposed a new extension of the Inverse Lindley distribution called “Lomax-Inverse Lindley distribution” which is more flexible compared to the Inverse Lindley distribution and other similar models. The paper derives and discusses some Statistical properties of the new distribution which include the limiting behavior, quantile function, reliability functions and distribution of order statistics. The parameters of the new model are estimated by method of maximum likelihood estimation. Conclusively, three lifetime datasets were used to evaluate the usefulness of the proposed model and the results indicate that the proposed extension is more flexible and performs better than the other distributions considered in this study.

scholarly journals Kumaraswamy Inverse Lindley Distribution with Stress-Strength Reliability

2020 ◽  
Vol 6 (3) ◽  
pp. 255-264
Author(s):  
Saeed E. HEMEDA ◽  
Sukanta PRAMANİK ◽  
Sudhansu S MAİTİ
Keyword(s):  
Lindley Distribution ◽  
Inverse Lindley Distribution

scholarly journals On the extension of inverse Lindley distribution

2021 ◽  
Vol 15 (2) ◽  
pp. 205-220
Author(s):  
Vikas Kumar Sharma ◽  
Pragya Khandelwal
Keyword(s):  
Lindley Distribution ◽  
Inverse Lindley Distribution

scholarly journals Estimation of Stress Strength Reliability in Single Component Models for Different Distributions

2019 ◽  
pp. 1-10
Author(s):  
Nafeesa Bashir ◽  
Raeesa Bashir ◽  
T. R. Jan ◽  
Shakeel A. Mir
Keyword(s):  
Likelihood Estimation ◽  
Inverse Power ◽  
Reliability Parameter ◽  
Strength Parameters ◽  
Lindley Distribution ◽  
Power Lindley Distribution ◽  
Method Of Maximum Likelihood ◽  
R Programming ◽  
Component Models ◽  
Inverse Lindley Distribution

This paper aims to estimate the stress-strength reliability parameter R = P(Y < X), considering the two different cases of stress strength parameters, when the strength ‘X’ follows exponentiated inverse power Lindley distribution ,extended inverse Lindley and Stress ‘Y’ follows inverse power Lindley distribution and inverse Lindley distribution. The method of maximum likelihood estimation is used to obtain the reliability estimators. Illustrations are provided using R programming.

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