A new extension of Lindley distribution: modified validation test, characterizations and different methods of estimation

By Mohamed Ibrahim, Abhimanyu Singh Yadav, Haitham M. Yousof, Hafida Goual, G. Hamedani. Communications for Statistical Applications and Methods, 2019

81 citations recorded by the source corpus.

In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical / mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through di ff erent classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

Subfields: Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9079a8e9afbf88b06c47aff378ea0ac0cc5fd6b5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Nadeem Shafique Butt
2. Haitham M. Yousof
3. G. Hamedani
4. Ahmed Z. Afify

In Statistics and Probability

1. Nadeem Shafique Butt
2. Haitham M. Yousof
3. Mohamed Ibrahim
4. Mahmoud M. M. Mansour
5. S. Ansari
6. G. Hamedani
7. Ahmed Z. Afify
8. Morad Alizadeh

Citations in the corpus

• A Generalization of Reciprocal Exponential Model: Clayton Copula, Statistical Properties and Modeling Skewed and Symmetric Real Data Sets (2020, background): “…data sets can be found and analyzed (see Basikhasteh et al. (2018), Elbiely and Yousof (2018 and 2019), Khalil et al. (2019), Gad et al. (2019), Ibrahim et al. (2019), Ibrahim (2019, 2020a, b), Ibrahim et al. (2020), Ibrahim and Yousof (2020), Mansour et al. (2020) and Al-Babtain et al.…”