Have a personal or library account? Click to login
Time Series Forecast Intervals using Circular Bootstrapped Training Simulation with Invariant Distance KNN Cover

Time Series Forecast Intervals using Circular Bootstrapped Training Simulation with Invariant Distance KNN

International Journal of Applied Mathematics and Computer Science
Volume 36 (2026): Issue 1 (March 2026)
By: Patchanok Srisuradetchai and  Parattakorn Kamlangdee  
Open Access
|Mar 2026

Authors

Patchanok Srisuradetchai

patchanok@mathstat.sci.tu.ac.th

Faculty of Science and Technology, Thammasat University Khlong Luang, Pathum Thani, Thailand

Parattakorn Kamlangdee

parattakorn.kaml@dome.tu.ac.th

Faculty of Science and Technology, Thammasat University Khlong Luang, Pathum Thani, Thailand
DOI: https://doi.org/10.61822/amcs-2026-0009 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Journal RSS Feed
Language: English
Page range: 113 - 127
Submitted on: Jun 12, 2025
|
Accepted on: Dec 15, 2025
|
Published on: Mar 21, 2026
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
K-nearest neighbors,
circular block bootstrapping,
uncertainty quantification,
rolling-window forecasting
Related subjects:
Mathematics,
Applied mathematics

© 2026 Patchanok Srisuradetchai, Parattakorn Kamlangdee, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Previous articleVolume 36 (2026): Issue 1 (March 2026)Next article