针对泊松或伽马分布数据的两阶段实验试验的贝叶斯预测模型

IF 0.6 Q4 STATISTICS & PROBABILITY

Electronic Journal of Applied Statistical Analysis Pub Date : 2020-02-05 DOI:10.1285/I20705948V13N1P268

Houda Bourezaz, H. Merabet, P. Druilhet

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引用次数: 0

摘要

我们考虑贝叶斯预测模型来评估第一阶段实验后的满意度指数，以便决定在第二阶段停止或继续。我们将这种方法应用于泊松和伽玛分布结果在许多领域，如可靠性或生存分析早期终止由于无效或有效。我们研究两种决策:混合贝叶斯-频率方法或全贝叶斯方法。

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Bayesian prediction modelling for two-stage experimental trials for Poisson or Gamma distributed data

We consider Bayesian prediction modelling to evaluate a satisfaction index after a first phase of experiment in order to decide to stop or continue at the second stage. We apply this method to Poisson and Gamma distributed outcomes in many fields such as reliability or survival analysis for early termination due to either futility or efficacy. We look at two kinds of decisions making: an hybrid Bayesian-frequentist or a full Bayesian approach.

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来源期刊

Electronic Journal of Applied Statistical Analysis STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

14.30%

发文量