Comparison of predictive effect between the single auto regressive integrated moving average (ARIMA) model and the ARIMA-generalized regression neural network (GRNN) combination model on the incidence of scarlet fever
10.3760/cma.j.issn.0254-6450.2009.09.025
- VernacularTitle:单纯ARIMA模型和ARIMA-GRNN组合模型在猩红热发病率中的预测效果比较
- Author:
Yu ZHU
1
;
Jie-Lai XIA
;
Jing WANG
Author Information
1. 安徽医科大学
- Keywords:
Scarlet fever;
Auto regressive integrated moving average model;
Generalized regression neural network
- From:
Chinese Journal of Epidemiology
2009;30(9):964-968
- CountryChina
- Language:Chinese
-
Abstract:
R2) of the two models were 0.801,0.872 respectively. The fitting efficacy of the ARIMA-GRNN combination model was better than the single ARIMA, which had practical value in the research on time series data such as the incidence of scarlet fever.
