Bayesian Estimation and Prediction for Exponentiated Generalized Inverted Kumaraswamy Distribution Based on Dual Generalized Order Statistics

Autor: A. M. Abd Al-Fattah, G. R. Al-Dayian, R. E. Abd El-Kader, Abeer Abd-Alla EL-Helbawy
Rok vydání: 2021
Předmět:
Zdroj: Journal of Advances in Mathematics and Computer Science. :94-111
ISSN: 2456-9968
DOI: 10.9734/jamcs/2021/v36i130334
Popis: In this paper, the shape parameters, reliability and hazard rate functions of the exponentiated generalized inverted Kumaraswamy distribution are estimated using Bayesian approach. The Bayes estimators are derived under the squared error loss function and the linear-exponential loss function based on dual generalized order statistics. Credible intervals for the parameters, reliability and hazard rate functions are obtained. The Bayesian prediction (point and interval) for a future observation of the exponentiated generalized inverted Kumaraswamy distribution is obtained based on dual generalized order statistics. All results are specialized to lower record values and a numerical study is presented. Moreover, the theoretical results are applied on three real data sets.
Databáze: OpenAIRE