Minimum Mean Squared Error Estimation of the Noise in Unobserved Component Models
Minimum Mean Squared Error Estimation of the Noise in Unobserved Component Models
复制标题
未观测组件模型中噪声的最小均方误差估计
DOI：
10.1080/07350015.1987.10509566
复制
发表时间：
1987
期刊：
影响因子：
--
通讯作者：
A. Maravall
中科院分区：
文献类型：
--
作者：
A. Maravall
在基于模型的未观测分量估计中，噪声分量的最小均方误差估计不同于白色噪声。在这篇文章中，一些差异进行了分析。可以看出，分量的方差总是被低估，并且噪声方差越小，低估越大。小方差噪声分量的估计器也将具有大的自相关。最后，在应用程序的上下文中，估计的噪声的样本自相关函数被认为是执行以及作为诊断工具，即使当方差是小的，系列是相对较短的长度。
In model-based estimation of unobserved components, the minimum mean squared error estimator of the noise component is different from white noise. In this article, some of the differences are analyzed. It is seen how the variance of the component is always underestimated, and the smaller the noise variance, the larger the underestimation. Estimators of small-variance noise components will also have large autocorrelations. Finally, in the context of an application, the sample autocorrelation function of the estimated noise is seen to perform well as a diagnostic tool, even when the variance is small and the series is of relatively short length.