Functional Principal Component Analysis for Cointegrated Functional Time Series
Methodology
2023-04-18 v8 Econometrics
Statistics Theory
Statistics Theory
Abstract
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.
Keywords
Cite
@article{arxiv.2011.12781,
title = {Functional Principal Component Analysis for Cointegrated Functional Time Series},
author = {Won-Ki Seo},
journal= {arXiv preprint arXiv:2011.12781},
year = {2023}
}