论文标题
协同功能时间序列的功能主成分分析
Functional Principal Component Analysis for Cointegrated Functional Time Series
论文作者
论文摘要
功能主成分分析（FPCA）在功能时间序列分析的开发中发挥了重要作用。本说明研究了如何使用FPCA来分析协整的功能时间序列，并提出将FPCA作为一种新型统计工具的修改。我们修改的FPCA不仅为协调向量提供了渐近更有效的估计量，而且还导致了基于FPCA的新型测试，用于检查协调功能时间序列的基本特性。
Functional principal component analysis (FPCA) has played an important role in the development of functional time series analysis. This note investigates how FPCA can be used to analyze cointegrated functional time series and proposes a modification of FPCA as a novel statistical tool. Our modified FPCA not only provides an asymptotically more efficient estimator of the cointegrating vectors, but also leads to novel FPCA-based tests for examining essential properties of cointegrated functional time series.
