Bayesian analysis for the Lomax model using noninformative priors  

作　　者：Daojiang He Dongchu Sun Qing Zhu 

机构地区：[1]Department of Statistics,Anhui Normal University,Wuhu,People’s Republic of China [2]Department of Statistics,University of Nebraska-Lincoln,Lincoln,NE,USA

出　　处：《Statistical Theory and Related Fields》2023年第1期61-68,共8页统计理论及其应用（英文）

基　　金：the National Social Science Foundation of China(Grant No.21BTJ034).

摘　　要：The Lomax distribution is an important member in the distribution family.In this paper,we systematically develop an objective Bayesian analysis of data from a Lomax distribution.Noninformative priors,including probability matching priors,the maximal data information(MDI)prior,Jeffreys prior and reference priors,are derived.The propriety of the posterior under each prior is subsequently validated.It is revealed that the MDI prior and one of the reference priors yield improper posteriors,and the other reference prior is a second-order probability matching prior.A simulation study is conducted to assess the frequentist performance of the proposed Bayesian approach.Finally,this approach along with the bootstrap method is applied to a real data set.

关 键 词：Lomax model probability matching priors MDI prior Jeffreys prior reference priors posterior propriety 

分 类 号：O175[理学—数学]