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Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, <t>Bayesian</t> <t>structural</t> <t>time</t> <t>series</t> without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average <t>model</t> for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance
G Bayesian Structural Time Series Model, supplied by Baidu Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/g bayesian structural time series model/product/Baidu Inc
Average 86 stars, based on 1 article reviews
g bayesian structural time series model - by Bioz Stars, 2026-06
86/100 stars

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Article Title: Early warning of hepatitis B epidemics in Henan Province, China, from 2014 to 2023 based on Baidu Index and Bayesian Structural Time Series model

Journal: Archives of Public Health

doi: 10.1186/s13690-026-01837-y

Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, Bayesian structural time series without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average model for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance
Figure Legend Snippet: Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, Bayesian structural time series without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average model for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance

Techniques Used: Comparison



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Baidu Inc g bayesian structural time series model
Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, <t>Bayesian</t> <t>structural</t> <t>time</t> <t>series</t> without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average <t>model</t> for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance
G Bayesian Structural Time Series Model, supplied by Baidu Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/g bayesian structural time series model/product/Baidu Inc
Average 86 stars, based on 1 article reviews
g bayesian structural time series model - by Bioz Stars, 2026-06
86/100 stars
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Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, Bayesian structural time series without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average model for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance

Journal: Archives of Public Health

Article Title: Early warning of hepatitis B epidemics in Henan Province, China, from 2014 to 2023 based on Baidu Index and Bayesian Structural Time Series model

doi: 10.1186/s13690-026-01837-y

Figure Lengend Snippet: Comparison of 12-month and 33-month ahead forecasts for monthly Hepatitis B incidence in Henan Province, China, 2014–2023, using seasonal autoregressive integrated moving average, seasonal autoregressive integrated moving average with exogenous variables, Bayesian structural time series without Baidu Index, and Bayesian structural time series with Baidu Index models. A Seasonal autoregressive integrated moving average model for 12-month ahead forecasts. B Seasonal autoregressive integrated moving average with exogenous variables model for 12-month ahead forecasts. C Bayesian structural time series model without Baidu Index for 12-month ahead forecasts. D Bayesian structural time series model with Baidu Index for 12-month ahead forecasts. E Seasonal autoregressive integrated moving average model for 33-month ahead forecasts. F Seasonal autoregressive integrated moving average with exogenous variables model for 33-month ahead forecasts. G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts. H Bayesian structural time series model with Baidu Index for 33-month ahead forecasts. The Bayesian structural time series models, especially with Baidu Index, demonstrate superior predictive performance

Article Snippet: G Bayesian structural time series model without Baidu Index for 33-month ahead forecasts.

Techniques: Comparison