Finite mixtures of covariance structure models with regressors - Loglikelihood function, minimum distance estimation, fit indices, and a complex example
Finite mixtures of covariance structure models with regressors - Loglikelihood function, minimum distance estimation, fit indices, and a complex example
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DOI：
10.1177/0049124197026002002
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发表时间：
1997-11-01
影响因子：
6.3
通讯作者：
Stein, P
中科院分区：
文献类型：
--
作者：
Arminger, G;Stein, P
模型的正常密度的条件回归变量的有限混合物的指定和估计。作者考虑多元正态混合，其中每个分量的期望值取决于非正态回归变量。混合成分的期望值和协方差矩阵使用条件均值和协方差结构参数化。作者讨论了似然函数的构造，并概述了参数的估计。此外，他们还定义了拟合指数，并讨论了特定于均值和协方差结构混合的模型规范和修改方面。最后，他们给出了一个实证的例子，他们分析了汽车对个人的重要性取决于潜在的结构，个人主义和生态意识。结果表明，所考虑的样本来自三个异质亚群。证明了每个子总体可能具有不同的均值和协方差结构。
Models of finite mixtures of normal densities conditional on regressor variables are specified and estimated. The authors consider mixtures of multivariate normals where the expected value for each component depends on nonnormal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean-and covariance-structures. The authors discuss the construction of the likelihood function and outline the estimation of parameters. in addition, they define fit indices and discuss aspects of model specification and modification that are specific to mixtures of mean- and covariance-structures. Finally they give an empirical example in which they analyze the importance of automobiles to individuals depending on the latent constructs individualism and ecology-mindedness. It is shown that the sample under consideration comes from three heterogeneous subpopulations. It is demonstrated that each subpopulation may he characterized by a different mean-and covariance-structure.