Adaptive estimation in time-series models
Adaptive estimation in time-series models
复制标题
时间序列模型中的自适应估计
DOI：
10.1214/aos/1031833674
复制
发表时间：
1997
期刊：
影响因子：
--
通讯作者：
B. Werker
中科院分区：
文献类型：
--
作者：
F. C. Drost;C. Klaassen;B. Werker
在一个特别适合于许多时间序列模型的框架中，我们在相当自然和经济的条件下获得了LAN结果。这使我们能够构建自适应估计（部分）的欧几里德参数在这些半参数模型。特别注意的是针对组模型的时间序列与模型的重要子类随时间变化的位置和规模。我们的设置是面对现有的文献，作为例子，我们重新考虑线性回归和阿尔马，TAR和ARMA模型。
In a framework particularly suited for many time-series models we obtain a LAN result under quite natural and economical conditions. This enables us to construct adaptive estimators for (part of) the Euclidean parameter in these semiparametric models. Special attention is directed to group models in time series with the important subclass of models with time varying location and scale. Our set-up is confronted with the existing literature and, as examples, we reconsider linear regression and ARMA, TAR and ARCH models.