Distributed ARIMA models for ultra-long time series

Xiaoqian Wang, Yanfei Kang, Rob J. Hyndman, Feng Li

Open source

DOI: 10.1016/j.ijforecast.2022.05.001
Published: 2023-07
Container: International Journal of Forecasting
Publisher: Elsevier BV
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1016/j.ijforecast.2022.05.001,
  title = {Distributed ARIMA models for ultra-long time series},
  author = {Xiaoqian Wang and Yanfei Kang and Rob J. Hyndman and Feng Li},
  year = {2023},
  journal = {International Journal of Forecasting},
  doi = {10.1016/j.ijforecast.2022.05.001},
  url = {https://doi.org/10.1016/j.ijforecast.2022.05.001}
}

RIS

TY  - JOUR
TI  - Distributed ARIMA models for ultra-long time series
AU  - Xiaoqian Wang
AU  - Yanfei Kang
AU  - Rob J. Hyndman
AU  - Feng Li
PY  - 2023
JO  - International Journal of Forecasting
DO  - 10.1016/j.ijforecast.2022.05.001
UR  - https://doi.org/10.1016/j.ijforecast.2022.05.001
ER  -

APA

Wang, X., Kang, Y., Hyndman, R. J., & Li, F. (2023). Distributed ARIMA models for ultra-long time series. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2022.05.001

Source records

crossref · retrieved 2026-11-09T06:39:44.520Z