Model misspecification
Model misspecification
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作者：
T. Tarpey;Dong Yun;E. Petkova
统计建模中的一个常见问题是区分有限混合分布和均匀非混合分布。有限混合模型在实际中被广泛使用，通常正常密度的混合和均匀的非正常密度的混合是难以区分的。本文说明了当正态混合的EM算法应用于均匀非混合分布的分布时会发生什么。特别是，引入了一种基于总体的有限混合EM算法，并将其直接应用于密度函数而不是样本数据。该算法被用来寻找常见均匀分布的有限混合近似。关于药物治疗抑郁症受试者的安慰剂反应的性质的一个例子被用来说明想法。
A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities. This paper illustrates what happens when the EM algorithm for normal mixtures is applied to a distribution that is a homogeneous non-mixture distribution. In particular, a population-based EM algorithm for finite mixtures is introduced and applied directly to density functions instead of sample data. This algorithm is used to find finite mixture approximations to common homogeneous distributions. An example regarding the nature of a placebo response in drug treated depressed subjects is used to illustrate ideas.
影响因子：
7
作者：
Bauer, DJ;Curran, PJ
通讯作者：
Curran, PJ