论文标题
在复杂趋势下的时变自动协方差的估计和推断：一种基于差异的方法
Estimation and Inference of Time-Varying Auto-Covariance under Complex Trend: A Difference-based Approach
论文作者
论文摘要
我们提出了一种基于差异的非参数方法，用于估计和推断本地固定时间序列的随时间变化的自动辅助功能，并被突然和平滑变化的复杂趋势污染时。在复杂趋势下，构建了具有渐近覆盖概率的同时置信带（SCB）。提出了一种模拟辅助引导方法，以实现SCB的实际结构。详细的仿真和一个真实的数据示例填写了我们的演示文稿。
We propose a difference-based nonparametric methodology for the estimation and inference of the time-varying auto-covariance functions of a locally stationary time series when it is contaminated by a complex trend with both abrupt and smooth changes. Simultaneous confidence bands (SCB) with asymptotically correct coverage probabilities are constructed for the auto-covariance functions under complex trend. A simulation-assisted bootstrapping method is proposed for the practical construction of the SCB. Detailed simulation and a real data example round out our presentation.
