A sustainable generalization of inverse Lindley distribution for wind speed analysis in certain regions of Pakistan

Author(s):  
Muhammad Shoaib ◽  
Irum Sajjad Dar ◽  
Muhammad Ahsan-ul-Haq ◽  
Rana Muhammad Usman
Author(s):  
Terna Godfrey Ieren ◽  
Peter Oluwaseun Koleoso ◽  
Adana’a Felix Chama ◽  
Innocent Boyle Eraikhuemen ◽  
Nasiru Yakubu

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.


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

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

Author(s):  
Nafeesa Bashir ◽  
Raeesa Bashir ◽  
T. R. Jan ◽  
Shakeel A. Mir

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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