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GARCH模型在门诊量预测中的应用
引用本文:郭毓鹏,关红军,荣胜忠,崔新宇,李淼晶,李晓霞. GARCH模型在门诊量预测中的应用[J]. 中国病案, 2013, 0(10): 42-45
作者姓名:郭毓鹏  关红军  荣胜忠  崔新宇  李淼晶  李晓霞
作者单位:牡丹江市,黑龙江省牡丹江医学院公共卫生学院流行病与卫生统计学教研室
基金项目:牡丹江医学院科学技术研究项目资助编号:2011-22157011
摘    要:应用GARCH模型理论分析某医院2003年至2012年月门诊量变化趋势,并建立AR(1)-IGARCH(2,1)模型,比较2003年至2012年月门诊实测值和模型预测值,其平均相对误差为0.057%,然后应用AR(1)-IGARCH(2,1)模型预测了2013年和2014年该院的月门诊量,比较2013年1月至6月月门诊量实测值和模型预测值,其平均相对误差为0.67%.分析结果表明GARCH模型能很好地追踪门诊量变化趋势.

关 键 词:GARCH模型  门诊量  预测

Application of GARCH Model in The Forecasting of Hospital Outpatient Numbers
Guo Yupeng,Guan Hongjun,Rong Shengzhong,Cui Xinyu,Li Miaojing,Li Xiaoxia. Application of GARCH Model in The Forecasting of Hospital Outpatient Numbers[J]. Chinese Medical Record, 2013, 0(10): 42-45
Authors:Guo Yupeng  Guan Hongjun  Rong Shengzhong  Cui Xinyu  Li Miaojing  Li Xiaoxia
Affiliation:Guo Yupeng,Guan Hongjun,Rong Shengzhong,Cui Xinyu,Li Miaojing,Li Xiaoxia
Abstract:To analyze the change trend of the monthly outpatient numbers from 2003 to 2012 of a hospital using the GARCH model theory, and build an AR (1) - IGARCH(2,1) model, then compared the actual numbers and the forecast numbers from 2003 to 2012, the average relative error is 0.057%. To forecast the monthly outpatient numbers of the following 2 years with the applica- tion of AR (1) - IGARCH (2, 1) model, and then compare the actual numbers and the forecast numbers date from January to June in 2013, the average relative error is 0.67%. The result indicated that the GARCH model was a good tool in closely tracing the change of monthly outpatient numbers.
Keywords:GARCH model  Outpatient number  Forecast
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