Time Series Forecast Intervals using Circular Bootstrapped Training Simulation with Invariant Distance KNN
This paper presents a nonparametric interval forecasting method that combines circular block bootstrap resampling with complexity-invariant K-nearest-neighbor time-series prediction. Prediction intervals are obtained directly from bootstrap-resampled training series, thereby preserving temporal depe...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Sciendo
2026-03-01
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| Serie: | International Journal of Applied Mathematics and Computer Science |
| Soggetti: | |
| Accesso online: | https://doi.org/10.61822/amcs-2026-0009 |
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