非线性联合均值方差模型的统计分析
Statistical Analysis for Nonlinear Joint Mean and Variance Models

作者: 周梦齐 , 徐登可 , 杨佳红 , 王梦滢 :浙江农林大学统计系,杭州;

关键词: 非线性联合均值方差模型异方差Gauss-Newton极大似然估计Nonlinear Joint Mean and Variance Models Heteroscedasticity Gauss-Newton Maximum Likelihood Estimate

摘要:

在提出非线性均值方差模型的基础上,研究了该模型中未知参数的估计问题。主要是基于Gauss-Newton迭代算法给出该模型中未知参数的极大似然估计。通过大量随机模拟实验验证了所提出方法的有效性。最后,结合实际问题数据验证了该模型与方法具有实用性和可行性。

Abstract: We propose nonlinear joint mean and variance models in this paper and investigate the estimate for unknown parameters in the model based on Gauss-Newton iterative algorithm. Furthermore, we make some simulations to show that the proposed procedure works satisfactorily. Lastly, two real examples are presented to illustrate the proposed methodology.

文章引用: 周梦齐 , 徐登可 , 杨佳红 , 王梦滢 (2014) 非线性联合均值方差模型的统计分析。 统计学与应用, 3, 68-75. doi: 10.12677/SA.2014.32010

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