首页>
外文期刊>statistics and computing
>Probability model choice in single samples from exponential families using Poisson log-linear modelling, and model comparison using Bayes and posterior Bayes factors
【24h】
Probability model choice in single samples from exponential families using Poisson log-linear modelling, and model comparison using Bayes and posterior Bayes factors
This paper describes a method due to Lindsey (1974a) for fitting different exponential family distributions for a single population to the same data, using Poisson log-linear modelling of the density or mass function. The method is extended to Efron's (1986) double exponential family, giving exact ML estimation of the two parameters not easily achievable directly. The problem of comparing the fit of the non-nested models is addressed by both Bayes and posterior Bayes factors (Aitkin, 1991). The latter allow direct comparisons of deviances from the fitted distributions.
展开▼
机译:本文描述了一种由于Lindsey(1974a)使用密度或质量函数的泊松对数线性建模,将单个种群的不同指数族分布拟合到相同数据的方法。该方法扩展到 Efron (1986) 的双指数族,对两个不容易直接实现的参数进行精确的 ML 估计。比较非嵌套模型拟合的问题由贝叶斯因子和后验贝叶斯因子解决(Aitkin,1991)。后者允许直接比较与拟合分布的偏差。
展开▼