混合非线性联合均值与方差模型的统计推断
Mixture of Nonlinear for Joint Mean and Variance Models
在异质总体中, 混合回归模型是最重要的统计数据分析工具之一. 提出了混合非线性联合均值与方差模型, 通过EM算法研究了该模型参数的极大似然估计, 并通过随机模拟实验验证了所提出方法的有效性. 最后, 结合实际数据验证了该模型和方法具有实用性和可行性.
Mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. We propose mixture of nonlinear for joint mean and variance models in this paper and investigate the maximum likelihood estimate for unknown parameters based on expectation maximization (EM) algorithm. Furthermore, we make some simulations to show that the proposed procedure works satisfactorily. Finally, a real example is presented to illustrate the proposed methodology.
混合非线性联合均值与方差模型 / EM算法 / 极大似然估计 / 异质总体. {{custom_keyword}} /
/
〈 | 〉 |