A new estimation in functional linear concurrent model with covariate dependent and noise contamination
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s00184-023-00900-w.pdf
Reference36 articles.
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2. Bosq D (2012) Linear processes in function spaces: theory and applications, vol 149. Springer Science and Business Media
3. Bücher A, Dette H, Heinrichs F (2019) Detecting deviations from second-order stationarity in locally stationary functional time series. Annals of the Institute of Statistical Mathematics pp 1–40
4. Cerqueira V, Torgo L, Mozetič I (2020) Evaluating time series forecasting models: an empirical study on performance estimation methods. Mach Learn 109(11):1997–2028
5. Chang J, Chen C, Qiao X, Yao Q (2022) An autocovariance-based learning framework for high-dimensional functional time series, arXiv:2008.12885v3
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