Estimation Based on Generalized Order Statistics from the Burr Model

51 citations recorded by the source corpus.

How researchers see this paper

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

Classical and Bayesian estimation of $$P(X<Y)$$P(X<Y) using upper record values from Kumaraswamy’s distribution (2014, unknown): “…+ δ2, 1 − λ2λ1 , v) ]) if λ2 ≤ λ1 , (28) where c2 = δ1 ln( λ1λ2 ) and c3 = δ2 ln( λ2λ1 ) − v. Alternatively, we consider using the approximation of Lindley (1980) and following the approach of Jaheen (2005), it can be easily seen that the approximate Bayes estimate of R under the SE and LINEX…”
E-Bayesian estimation for the Burr type XII model based on type-2 censoring (2011, methodology): “Jaheen [11] used the generalized order statistics for obtaining Bayesian inference for the Burr XII model.”