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- W3159958884 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." @default.
- W3159958884 created "2021-05-10" @default.
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- W3159958884 date "2023-06-23" @default.
- W3159958884 modified "2023-10-14" @default.
- W3159958884 title "Functional principal component analysis for cointegrated functional time series" @default.
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- W3159958884 doi "https://doi.org/10.1111/jtsa.12707" @default.
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