Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
In this study, the maximum likelihood and approximate Bayes estimators to the reliability function of two parameter Lindley distribution have been derived when the data are shown in fuzzy form. Bayes estimators have been derived based on informative gamma priors with squared error and precautionary loss functions according to approximate Lindley’s technique. The generated samples that follow the two parameter Lindley distribution are converted to fuzzy data based on a specific fuzzy information system. In addition, obtained estimators to the reliability function have been compared numerically through a Monte-Carlo simulation study in terms of their integrated mean squared error values.
How to cite this article:
Nadia Hashim Al-Noor and Rasha Sameer Subhi. Two Parameter Lindley Distribution:Estimating the Reliability Function with
Fuzzy Data.
DOI: https://doi.org/10.36478/jeasci.2018.7670.7676
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.7670.7676