移动自回归模型的应用实例分析.doc

文档介绍：大连海事大学
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毕业论文


二○一三年六月





移动自回归模型
的应用实例分析












专业班级:数学与应用数学2009 -1班
姓名: 田赟
指导教师: 卢玉贞(副教授)








数学系

二○一三年六月

摘要
时间序列分析以随机过程理论作为数学基础,应用概率统计的理论和方法来分析、处理平稳数据序列。时间序列分析的目的是利用历史数据序列进行分析,找出其变化规律和发展趋势并建立数学模型,最终利用模型预测序列的未来。常用的平稳时间序列模型有AR模型、MA模型和ARMA混合模型。
国内生产总值(GDP)是衡量一个国家经济状况的重要指标,它对反映国家的经济发展状态、国民收入和消费能力的情况起着重要作用。一个国家的发展情况如何,主要看GDP。而人均GDP主要用来衡量一个。对于经济发展迅速的我均生活水平情况。
本文基于ARMA模型及其相关模型理论知识,通过对我国过去35年的人均GDP进行时间序列分析,建立数学模型,对模型进行识别、拟合和诊断,选择最优模型,最后还对未来三年的人均GDP进行了大胆预测。
关键词:时间序列;ARMA模型;预测;人均GDP
ABSTRACT
Time series analysis is based on random process theory as the mathematical basis, and it applies the probability and statistics theory and method to analyze and process the stationary data sequence. The purpose of time series analysis is to analyze the historical data sequence, to find out the change rule and the trend of development, and to establish mathematical model, in the end, to forecast the future data by the model.
Gross domestic product (GDP) is an important indicator to measure a country's economic conditions. It plays an important role to reflect the country's economic development status, national e and consumption ability. How is the development of the country, basically see GDP. What’s more, per capita GDP is mainly used to measure a country people's living standard. Researching on rapid economic development of our country, per capita GDP is a helpful aid in getting to know the average standard of living of our people.
This paper was based on the theoretical knowledge of ARMA model and its related models, and by time series analyzing through our country's per capita GDP over the past 35 years, it established the mathematical models, then identified, fitted and diagnosed them, and selected the optimal one. Finally, I boldly predicted the per capita GDP for the next three years.
Keywords: Time Series ; ARMA Model ;