The effect of estimation of unknown degrees of freedom on estimation of remaining parameters in Spanos'conditional t heteroskedastic model
The effect of estimation of unknown degrees of freedom on estimation of remaining parameters in Spanos'conditional t heteroskedastic model
复制标题
Spanos条件t异方差模型中未知自由度估计对剩余参数估计的影响
DOI：
10.1080/03610918.2012.675112
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发表时间：
2013
影响因子：
0.9
通讯作者：
Jiro Hodoshima
中科院分区：
文献类型：
--
作者：
野村淳一;木下 真;朝日幸代;程島次郎;Jiro Hodoshima
本文研究了 Spanos 条件 t 异方差模型中未知自由度估计对剩余参数有效估计的影响。我们通过仿真比较了模型中剩余参数的三个最大似然估计器（MLE）：当所有参数都由 MLE 估计时、当自由度由矩估计器方法估计时以及当自由度指定错误时，其余参数的 MLE。与前一种方法相比，后两种方法在模型中推断方差参数方面表现较差。因此，通过 MLE 有效估计自由度对于有效估计剩余方差参数非常重要。
This article investigates the effect of estimation of unknown degrees of freedom on efficient estimation of remaining parameters in Spanos’ conditional t heteroskedastic model. We compare by simulation three maximum likelihood estimators (MLEs) of the remaining parameters in the model: the MLE of the remaining parameters when all the parameters are estimated by the MLE, when the degrees of freedom is estimated by a method of moments estimator, and when the degrees of freedom is erroneously specified. The latter two methods are found to perform poorly compared to the former method for the inference of variance parameters in the model. Thus, efficient estimation of degrees of freedom by the MLE is important to estimate efficiently the remaining variance parameters.