| fpcb-package {fpcb} | R Documentation |
Predictive confindence bands for functional time series forecasting
Description
Functions to represent functional objects under a Reproducing Kernel Hilbert Space (RKHS) framework as described in Muñoz & González (2010). <doi:10.1016/j.patrec.2009.07.014>. Autoregressive Hilbertian Model for functional time series using RKHS and predictive confidence bands construction as proposed in Hernández et al (2021) <arXiv:2105.13627>.
Author(s)
Nicolás Hernández [aut, cre], Jairo Cugliari [aut, cre]
Mantainer: Nicolás Hernández <nicolas.hernandez@mrc-bsu.cam.ac.uk>
References
A. Muñoz, J. González, Representing functional data using support vector machines, Pattern Recognition Letters 31 (2010) 511–516. <doi:10.1016/j.patrec.2009.07.014>.
Martos, G. et al (2018): Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection. Entropy 20(1): 33 (2018). <doi:10.3390/e20010033>.
D. Wang, Z. Zhao, R. Willett, C. Y. Yau, Functional autoregressive processes in reproducing kernel hilbert spaces, arXiv preprint arXiv:2011.13993 (2020).
N. Hernández, J. Cugliari, J. Jacques. Simultaneous Predictive Bands for Functional Time Series using Minimum Entropy Sets. arXiv:2105.13627 (2021).