文章基本信息

标题：Objective Bayesian Snalysis for the Complementary Exponential Geometric Model Applied to Cancer Data
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作者：Daniele Granzotto ; Vera Tomazella ; Francisco Louzada 等
期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2017
卷号：6
期号：2
页码：122
DOI：10.5539/ijsp.v6n2p122
出版社：Canadian Center of Science and Education
摘要：In this paper we provide a reference Bayesian framework to a new two-parameter lifetime distribution with increasing failure rate, the complementary exponential geometric (CEG). To this end, we presented some of the main properties of this model and its characteristics related to the reliability analysis. A simulation study is performed to analyse the frequentist properties of credible intervals from the reference posterior distribution among of the standard error and mean square error (MSE) of estimations. The presented methodology is illustrated by the use of a real data set which presents the study of time until the cure of cervix lesions, that are precursors cancer lesions in the cervix. According to to INCA (Cancer National Institute), cervical cancer stands as the fourth cause of death among women in Brazil. Together with breast cancer, it is one of the most common malignancy affecting women worldwide. For this reason, patients must be carefully evaluated for metastatic disease. These data were collected in the Woman Clinic which is sited in Maring\'{a} city (Paran\'{a} State, Brazil).