函数方差检验方法的应用

发布时间：2018-06-27 17:19

本文选题：方差分析 + 函数型数据　；参考：《统计与决策》2017年09期

【摘要】：空气污染问题引起了社会广泛关注,影响空气质量评价的因素有很多,研究这些因素对指标的影响是否都显著尤为重要。文章将函数型方差检验的方法(ANOVA)应用到空气质量的数据中,首先采集到北京市区内分布在不同地方的35个监测站的每天每小时的实时更新数据,对北京市划分的五个行政区域的空气污染成分进行函数方差分析的k样本均值假设检验,进而分析北京市各行政区域空气污染的各成分之间的差异。
[Abstract]:The problem of air pollution has aroused widespread concern in the society. There are many factors that affect the air quality evaluation. It is particularly important to study whether these factors have a significant impact on the indicators. In this paper, the method of functional variance test (ANOVA) is applied to air quality data. First of all, the daily real-time update data of 35 monitoring stations distributed in different places in Beijing are collected. The air pollution components of the five administrative regions in Beijing were tested by the k-sample mean hypothesis of the functional variance analysis, and then the differences between the air pollution components in the five administrative regions of Beijing were analyzed.
【作者单位】：首都经济贸易大学统计学院;哈尔滨师范大学数学科学学院;
【基金】：全国统计科学研究计划项目(2013LZ13) 黑龙江省青年基金资助项目(JJ2016QN0211) 北京特大城市研究中心资助项目(TDJD201502)
【分类号】：O212.1;X823

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