Abstract
This paper deals with simultaneous prediction for time series models. In particular, it presents a simple procedure which gives well-calibrated simultaneous prediction intervals with coverage probability close to the target nominal value. Although the exact computation of the proposed intervals is usually not feasible, an approximation can be easily attained by means of a suitable bootstrap simulation procedure. This new predictive solution is much simpler to compute than those ones already proposed in the literature, based on asymptotic calculations. Applications of the bootstrap calibrated procedure to AR, MA and ARCH models are presented.
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Acknowledgements
This research was partially supported by the University of Udine under the PRID2017 research grants and by the Italian Ministry for University and Research under the PRIN2015 Grant No. 2015EASZFS_003. Simulation studies were performed on SCSCF, a multiprocessor cluster system owned by Università Ca’ Foscari Venezia.
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Fonseca, G., Giummolè, F. & Vidoni, P. A note on simultaneous calibrated prediction intervals for time series. Stat Methods Appl 30, 317–330 (2021). https://doi.org/10.1007/s10260-020-00526-6
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DOI: https://doi.org/10.1007/s10260-020-00526-6