基于时间序列分析方法的胆囊炎发病率预测

基础医学与临床 ›› 2011, Vol. 31 ›› Issue (1): 9-12.

基于时间序列分析方法的胆囊炎发病率预测

马亮亮,田富鹏

西北民族大学计算机科学与信息工程学院

收稿日期:2010-04-19 修回日期:2010-05-12 出版日期:2011-01-05 发布日期:2011-01-05
通讯作者: 马亮亮

Time Series Analysis Method Applied in Prediction of Cholecystitis Incidence Rate

MA Liang-liang ¹,TIAN Fu-peng ²

1. School of Computer and Information, Northwest University for Nationalities2.

Received:2010-04-19 Revised:2010-05-12 Online:2011-01-05 Published:2011-01-05
Contact: MA Liang-liang

摘要/Abstract

摘要： 目的探讨时间序列分析方法在时间序列资料中的应用，建立海西州地区胆囊炎发病率的预测模型。方法在时间序列分析方法理论的基础上，通过时间序列模型对海西州地区的胆囊炎发病率进行实证研究，建立了相应的ARMA模型和ARCH模型并进行预测和评价。结果 ARCH模型的预测结果较ARMA模型理想，适合描述海西州地区胆囊炎发病率的变动趋势。结论 ARMA(4,2)-ARCH(2)模型可作为海西州地区胆囊炎发病率的预测模型。

关键词: ARMA模型, ARCH模型, 时间序列分析, 胆囊炎

Abstract: Objective The research aims to investigate the application of time series analysis method on time series datum, and establish forecasting model on cholecystitis incidence rate in Haixizhou region. Methods Based on the theory of time series model, through time series model some empirical studies into cholecystitis incidence rate have been made. ARMA and ARCH models are built to stimulate and forecast the pattern of the rate. Results The predicted result of ARCH model is more fitted than that of ARMA model and the ARCH model can describe the dynamic characteristics of cholecystitis incidence rate. Conclusion ARMA (4, 2)-ARCH (2) model can be used as the forecasting model of cholecystitis incidence rate in Haixizhou region.

中图分类号:

O212.4

马亮亮;田富鹏. 基于时间序列分析方法的胆囊炎发病率预测[J]. 基础医学与临床, 2011, 31(1): 9-12.

MA Liang-liang ;TIAN Fu-peng . Time Series Analysis Method Applied in Prediction of Cholecystitis Incidence Rate[J]. Basic & Clinical Medicine, 2011, 31(1): 9-12.