Nonlinear Regression in SARS Forecasting

CUI Heng-jian1; LI Zhong-lai1; YANG Hua2; LI Xiao-wen  2

doi:10.11834/jrs.20030402

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Nonlinear Regression in SARS Forecasting
Issue 4, Pages: 245-250(2003)
Published：2003
DOI： 10.11834/jrs.20030402
稿件说明：

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[1]崔恒建,李仲来,杨华,李小文.SARS疫情预测预报中的分段非线性回归方法[J].遥感学报,2003(04):245-250. DOI： 10.11834/jrs.20030402.

CUI Heng-jian1, LI Zhong-lai1, YANG Hua2, et al. Nonlinear Regression in SARS Forecasting[J]. Journal of Remote Sensing, 2003, (4): 245-250. DOI： 10.11834/jrs.20030402.

摘要

介绍了几种对累计SARS疫情预测预报中的非线性增长曲线模型

说明了Richards增长曲线在这次SARS疫情预测预报中合理性和可行性

由此建立了累计SARS疫情预测预报中的非线性回归点模型。并具体对北京SARS疫情进行了跟踪预测预报

包括整体和分时间段的预测预报

获得了北京SARS疫情随时间的预测预报结果

说明了北京 4月底的一系列控制措施对北京SARS疫情所带来的影响

为进一步的后续研究打下了良好基础。

Abstract

This paper introduces some kinds of nonlinear growth curve for forecasting cumulative SARS patients

it is shown that the Richards curve is reasonable and flexible in this SARS forecasting. The nonlinear growth curve regression model is established for forecasting cumulative SARS patients.Specifically

the SARS situation forecasting in Beijing is made well which includes forecasting based on comsecutive and piecewise time fitting. It means some control policies in Beijing at the end of this April play important role for anti-spread of SARS

and also provides a good basis for future works.