论文标题
同时推断时间序列功能线性回归
Simultaneous Inference for Time Series Functional Linear Regression
论文作者
论文摘要
我们考虑关节同时置信带（JSCB）构建的问题，用于回归系数的时间序列函数，当回归模型通过粗糙度惩罚方法估算具有正向基础函数的灵活选择时估算回归模型时。为JSCB结构提出了一种简单而统一的乘数引导方法，该方法显示出渐近地实现正确的覆盖概率。此外，JSCB在模型的标准偏差上渐近地鲁棒性。所提出的方法将电力市场的时间序列数据集应用于视觉研究并正式测试整体回归关系以及执行模型验证。
We consider the problem of joint simultaneous confidence band (JSCB) construction for regression coefficient functions of time series scalar-on-function linear regression when the regression model is estimated by roughness penalization approach with flexible choices of orthonormal basis functions. A simple and unified multiplier bootstrap methodology is proposed for the JSCB construction which is shown to achieve the correct coverage probability asymptotically. Furthermore, the JSCB is asymptotically robust to inconsistently estimated standard deviations of the model. The proposed methodology is applied to a time series data set of electricity market to visually investigate and formally test the overall regression relationship as well as perform model validation.
