Rocha Ricardo, Nadarajah Saralees, Tomazella Vera, Louzada Francisco
Departamento de Estatística, Universidade Federal de São Carlos, São Carlos, SP, Brasil.
School of Mathematics, University of Manchester, Manchester, UK.
Lifetime Data Anal. 2016 Apr;22(2):216-40. doi: 10.1007/s10985-015-9328-x. Epub 2015 May 8.
The presence of immune elements (generating a fraction of cure) in survival data is common. These cases are usually modeled by the standard mixture model. Here, we use an alternative approach based on defective distributions. Defective distributions are characterized by having density functions that integrate to values less than 1, when the domain of their parameters is different from the usual one. We use the Marshall-Olkin class of distributions to generalize two existing defective distributions, therefore generating two new defective distributions. We illustrate the distributions using three real data sets.
生存数据中存在免疫因素(产生一定比例的治愈情况)很常见。这些情况通常用标准混合模型进行建模。在此,我们使用一种基于亏量分布的替代方法。亏量分布的特征是,当参数域与通常的不同时,其密度函数积分后的值小于1。我们使用马歇尔 - 奥尔金分布类来推广两个现有的亏量分布,从而生成两个新的亏量分布。我们用三个真实数据集来说明这些分布。