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Journal of Applied Statistics Volume 49, 2022 - Issue 5
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Research Article

Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models

Ufuk Beyaztasa Department of Economics and Finance, Piri Reis University University, Istanbul, TurkeyCorrespondence[email protected]
[email protected]
ORCID Iconhttps://orcid.org/0000-0002-5208-4950
ORCID Icon &
Han Lin Shangb Department of Actuarial Studies and Business Analytics, Macquarie University, Sydney, AustraliaORCID Iconhttps://orcid.org/0000-0003-1769-6430
ORCID Icon
Pages 1179-1202 | Received 09 May 2019, Accepted 23 Nov 2020, Published online: 01 Dec 2020

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Li Xue, Qiuyu Wang, Congkai Li & Lisheng An. (2023) Economic design of residuals MEWMA control chart with variable sampling intervals and sample size. Communications in Statistics - Simulation and Computation 0:0, pages 1-22.
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Samir Barman, Ramasubramanian V.Mrinmoy Ray. (2023) Improved Sieve Bootstrap based prediction intervals for time series. Communications in Statistics - Simulation and Computation 0:0, pages 1-21.
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Maria da Graça Ruano & Antonio Ruano. (2024) A Multi-Step Ensemble Approach for Energy Community Day-Ahead Net Load Point and Probabilistic Forecasting. Energies 17:3, pages 696.
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Qin Shao, Abdulaziz Aldhafeeri, Shuhao Qiu & Sadik Khuder. (2023) A multiplicative Holt–Winters model and autoregressive moving-average for hyponatremia mortality rates. Healthcare Analytics 4, pages 100262.
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Ufuk Beyaztas & Han Lin Shang. (2022) A robust partial least squares approach for function-on-function regression. Brazilian Journal of Probability and Statistics 36:2.
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