A comparative approach to analyzing and forecasting carbon dioxide emissions in ethiopia using Bayesian autoregressive integrated moving average (ARIMA) and Bayesian structural time series (BSTS) models.
- DOI
- 10.1186/s13021-026-00480-y
- Published
- 2026 Jul 7
- Container
- Carbon balance and management
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13021-026-00480-y,
title = {A comparative approach to analyzing and forecasting carbon dioxide emissions in ethiopia using Bayesian autoregressive integrated moving average (ARIMA) and Bayesian structural time series (BSTS) models.},
author = {Osman AA and Mengistie DT and Adawe DH and Figa RT and Marine BT},
year = {2026},
journal = {Carbon balance and management},
doi = {10.1186/s13021-026-00480-y},
url = {https://doi.org/10.1186/s13021-026-00480-y}
}RIS
TY - JOUR TI - A comparative approach to analyzing and forecasting carbon dioxide emissions in ethiopia using Bayesian autoregressive integrated moving average (ARIMA) and Bayesian structural time series (BSTS) models. AU - Osman AA AU - Mengistie DT AU - Adawe DH AU - Figa RT AU - Marine BT PY - 2026 JO - Carbon balance and management DO - 10.1186/s13021-026-00480-y UR - https://doi.org/10.1186/s13021-026-00480-y ER -
APA
AA, O., DT, M., DH, A., RT, F., & BT, M. (2026). A comparative approach to analyzing and forecasting carbon dioxide emissions in ethiopia using Bayesian autoregressive integrated moving average (ARIMA) and Bayesian structural time series (BSTS) models.. Carbon balance and management. https://doi.org/10.1186/s13021-026-00480-y
Source records
- pubmed · retrieved 2026-09-26T07:24:38.479Z