Modeling functional time series and mixed-type predictors with partially functional autoregression
10.1080/07350015.2021.2011299
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2024
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sg-nus-scholar.10635-2482402024-05-06T02:53:53Z Modeling functional time series and mixed-type predictors with partially functional autoregression Xiaofei Xu Ying Chen Ge Zhang Thorsten Koch STATISTICS & APPLIED PROBABILITY 10.1080/07350015.2021.2011299 Journal of Business & Economic Statistics 42 2 349-366 2024-05-06T02:53:52Z 2024-05-06T02:53:52Z 2022-02-02 Article Xiaofei Xu, Ying Chen, Ge Zhang, Thorsten Koch (2022-02-02). Modeling functional time series and mixed-type predictors with partially functional autoregression. Journal of Business & Economic Statistics 42 (2) : 349-366. ScholarBank@NUS Repository. https://doi.org/10.1080/07350015.2021.2011299 0735-0015 https://scholarbank.nus.edu.sg/handle/10635/248240 Taylor & Francis Taylor & Francis |
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10.1080/07350015.2021.2011299 |
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STATISTICS & APPLIED PROBABILITY |
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STATISTICS & APPLIED PROBABILITY Xiaofei Xu Ying Chen Ge Zhang Thorsten Koch |
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Article |
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Xiaofei Xu Ying Chen Ge Zhang Thorsten Koch |
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Xiaofei Xu Ying Chen Ge Zhang Thorsten Koch Modeling functional time series and mixed-type predictors with partially functional autoregression |
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Xiaofei Xu |
title |
Modeling functional time series and mixed-type predictors with partially functional autoregression |
title_short |
Modeling functional time series and mixed-type predictors with partially functional autoregression |
title_full |
Modeling functional time series and mixed-type predictors with partially functional autoregression |
title_fullStr |
Modeling functional time series and mixed-type predictors with partially functional autoregression |
title_full_unstemmed |
Modeling functional time series and mixed-type predictors with partially functional autoregression |
title_sort |
modeling functional time series and mixed-type predictors with partially functional autoregression |
publisher |
Taylor & Francis |
publishDate |
2024 |
url |
https://scholarbank.nus.edu.sg/handle/10635/248240 |
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