In this paper we develop approximate Bayes estimators of the two parameters logistic distribution. Lindley’s approximation and importance sampling techniques are applied. The Gaussian-gamma prior distribution and progressively type-II censored samples are assumed. Quadratic, linex and general entropy loss functions are used. The statistical performances of the Bayes estimates under quadratic, linex and general entropy loss functions are compared with those of the maximum likelihood estimators based on simulation study.
Digital Object Identifier (DOI)
Rashad, A.; Mahmoud, M.; and Yusuf, M.
"Bayes Estimation of the Logistic Distribution Parameters Based on Progressive Sampling,"
Applied Mathematics & Information Sciences: Vol. 10
, Article 32.
Available at: https://dc.naturalspublishing.com/amis/vol10/iss6/32