论文标题
时间序列中部分线性模型的同时推断
Simultaneous Inference of a Partially Linear Model in Time Series
论文作者
论文摘要
我们引入了一种新方法，以在部分线性时间序列回归模型中同时推断非参数分量，其中非参数部分是多元未知函数。特别是，我们通过将高维高斯近似值扩展到具有连续索引集的依赖过程来构造多元函数的同时置信区（SCR）。与以前的工作相比，我们的结果允许更普遍的依赖性结构，并且广泛适用于各种线性和非线性自回旋过程。我们通过在仿真研究中检查有限样本的性能来证明我们提出的方法的有效性。最后，提出了时间序列的应用程序序列，即远期保费回归，我们从汇率和宏观经济数据中为外汇风险溢价构建了SCR。
We introduce a new methodology to conduct simultaneous inference of the nonparametric component in partially linear time series regression models where the nonparametric part is a multivariate unknown function. In particular, we construct a simultaneous confidence region (SCR) for the multivariate function by extending the high-dimensional Gaussian approximation to dependent processes with continuous index sets. Our results allow for a more general dependence structure compared to previous works and are widely applicable to a variety of linear and nonlinear autoregressive processes. We demonstrate the validity of our proposed methodology by examining the finite-sample performance in the simulation study. Finally, an application in time series, the forward premium regression, is presented, where we construct the SCR for the foreign exchange risk premium from the exchange rate and macroeconomic data.
