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A Bayesian study for the comparison of generalized gamma model with its components

机译:贝叶斯研究,用于比较广义伽玛模型及其组成部分

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Generalized gamma distribution offers a flexible family and many of the important lifetime models are obtained as component models by setting its shape parameters to unity. The flexibility of the generalized gamma model, however, occurs at the cost of its increased complexity. The present paper makes a simulation based Bayesian study to have a thorough comparison of the generalized gamma with its components in situations where the given data appear compatible with this family. Of course, if a component model is recommended the latter inferences are quite easy to deal with. The study has been conducted in two stages. First, the generalized gamma family with a scale and two shape parameters is examined to see if one or both of its shape parameters can be set to unity in order that the component models can be looked upon as possible candidates. Second, a threshold parameter added in to the family selected at the first stage is tested against zero to see if there is any desirability of threshold in the model(s). A real data set is considered for the purpose of illustration. The paper proceeds by checking compatibility of the various component models with the given data set and finally compares the models to select the one that is most pertinent with the data.
机译:广义伽玛分布提供了一个灵活的族,并且通过将其形状参数设置为1获得许多重要的寿命模型作为组件模型。然而,广义伽玛模型的灵活性是以其增加的复杂性为代价的。本文进行了基于贝叶斯的模拟研究,以在给定数据看起来与该族兼容的情况下,对广义伽玛及其成分进行彻底的比较。当然,如果建议使用组件模型,则后面的推论很容易处理。该研究分两个阶段进行。首先,检查具有比例尺和两个形状参数的广义伽玛族,以查看是否可以将其形状参数中的一个或两个设置为统一,以便可以将组件模型视为可能的候选对象。其次,将添加到第一阶段选择的族中的阈值参数相对于零进行测试,以查看模型中是否存在阈值的合意性。为了说明的目的,考虑了真实的数据集。本文通过检查各种组件模型与给定数据集的兼容性来进行,最后比较模型以选择与数据最相关的模型。

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