时间序列分析方法及其进展

发布时间：2018-03-22 00:16

本文选题：时间序列模型　切入点：登革热病例　出处：《中国卫生统计》2015年06期 　论文类型：期刊论文

【摘要】：正在医学科研工作中,按某种(相等或不相等的)时间间隔对客观事物进行动态观察,由于随机因素的影响,各次观察的指标X_1,X_2,X_3,…,X_i,…都是随机变量,这种按时间顺序排列的一系列随机变量(或其观测值)称为时间序列。例如流行病学家会关注在某地区观察到的流感样病例数、登革热病例数随时间的变化,时间序列模型可以考虑时间对病例数的影响,亦可纳入不同的流行病学影响因素来预测病例数,以及探讨疫情季节性特征。
[Abstract]:In the course of medical scientific research, the objective things are dynamically observed at certain (equal or unequal) intervals. As a result of the influence of random factors, the indexes observed in each observation are: X _ _ _. This chronological sequence of random variables (or observations) is called a time series. For example, epidemiologists will focus on the number of influenza-like cases observed in a region, and the number of dengue fever cases over time. The time series model can take into account the influence of time on the number of cases, may also include different epidemiological factors to predict the number of cases, and to explore the seasonal characteristics of the epidemic situation.
【作者单位】：中山大学公共卫生学院医学统计与流行病学系;中山大学附属第一医院流行病学研究室;
【基金】：国家自然科学基金(30872182)
【分类号】：R181.2

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