A new parameter estimation method for the extended power Lindley distribution based on order statistics, with application

Devendra Kumar; Maneesh Kumar; Sapna Yadav; Anju Goyal

doi:https://doi.org/10.59170/stattrans-2024-020

A new parameter estimation method for the extended power Lindley distribution based on order statistics, with application

Devendra Kumar Department of Statistics, Central University of Haryana and Department of Statistics, Faculty of Mathematical Sciences, University of Delhi, Delhi, India ORCID:https://orcid.org/0000- 0001-5831-3315 , Maneesh Kumar Department of Statistics, Central University of Haryana, India ORCID:https://orcid.org/0000-0002-4186-5962 , Sapna Yadav Department of Statistics, Central University of Haryana, India ORCID:https://orcid.org/0009-0000-3143-3827 , Anju Goyal 4Department of Statistics, Panjab University, Chandigarh, India ORCID:https://orcid.org/0000-0002-0171-3163 Statistics in Transition new series, vol. 25, 2024, 2, pages: 167-184 Published online: 5 June 2024 https://doi.org/10.59170/stattrans-2024-020 Citation: Kumar, D., Kumar, M., Yadav, S., Goyal, A., 2024. A new parameter estimation method for the extended power Lindley distribution based on order statistics, with application.Statistics in Transition new series, 25(2), pp. 167-184. https://doi.org/10.59170/stattrans-2024-020

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ABSTRACT

In this paper, we propose inference procedures for the estimation of parameters by using order statistics. First, we derive some new expressions for single and product moments of the order statistics from the extended power Lindley distribution. We then use these moments to obtain the best linear unbiased estimates (BLUEs) of the location and scale parameters based on Type-II right-censored samples. A real data set is analysed to illustrate the flexibility and importance of the model.

KEYWORDS

extended power Lindley distribution, order statistics, moments, best linear unbiased estimator

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