异方差帕克检验方法的改进  

Improvement in Park Heteroscedasticity Test

作　　者：谭馨 邓光明[1,2] TAN Xin;DENG Guang-ming(College of Science,Guilin University of Technology,Guilin 541006,China;Institute of Applied Statistics,Guilin University of Technology,Guilin 541006,China)

机构地区：[1]桂林理工大学理学院,广西桂林541006 [2]桂林理工大学应用统计研究所,广西桂林541006

出　　处：《统计与信息论坛》2019年第6期10-16,共7页Journal of Statistics and Information

基　　金：国家社会科学基金项目《空间定位抽样技术在民族地区经济调查中的理论及应用研究》(13BTJ009);国家自然科学基金项目《复合聚类网络同步能力的尺度可变性及其粗粒化方法研究》(61563013)

摘　　要：围绕传统的帕克检验方法展开研究,针对该方法在对多元线性回归模型进行异方差检验时工作量大、计算繁琐、异方差模型不够准确这一系列问题,提出运用主成分的思想,将得到的所有综合指标建立异方差模型,并对不同形式的数据条件进行研究,根据系数的显著性检验,给出了一种新的异方差检验方法。模拟数据和实例论证表明该检验方法更为快捷准确。It is focused on the traditional Park test here.Aim at solving a series of problems caused by the method in testing heteroscedasticity of multiple linear regression models,including heavy workload,cumbersome calculation and inaccurate heteroscedasticity model.The idea of principal component analysis to use all the obtained aggregative indicators establishing a heteroscedasticity model is proposed,and different forms of data conditions are studied.According to the significance test of coefficients,a new method of testing heteroscedasticity is given.The simulation data and example analysis show that the new test method calculates faster and more accurate.

关 键 词：帕克检验 多元线性回归模型 异方差 主成分 

分 类 号：O212[理学—概率论与数理统计]