数学
瑞利分布
吉布斯抽样
统计
推论
最大似然
贝叶斯概率
贝叶斯推理
样品(材料)
比例参数
计量经济学
人工智能
计算机科学
概率密度函数
色谱法
化学
作者
Mohammad Z. Raqab,Mohamed T. Madi
标识
DOI:10.1016/j.jspi.2011.04.016
摘要
In this paper, and based on a progressive type-II censored sample from the generalized Rayleigh (GR) distribution, we consider the problem of estimating the model parameters and predicting the unobserved removed data. Maximum likelihood and Bayesian approaches are used to estimate the scale and shape parameters. The Gibbs and Metropolis samplers are used to predict the life lengths of the removed units in multiple stages of the progressively censored sample. Artificial and real data analyses have been performed for illustrative purposes.
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