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Ordinary least square(OLS) regression models the relationship between vector of covariate and the conditional mean of a responsegiven.However,quantile regression models the relationship between covariateand the conditional quantiles of given.Taken together the ensemble of estimated conditional quantile offers a much more complete view of the effect of covariates on the location,scale and shape of the distribution of the response variable.It is especially useful in applications where people are interested in upper or lower quantiles of a response.In this paper we first introduce the concept of quantile regression,then provide some brief methods about estimation,hypothesis tests and goodness-of-fit of quantile regression,some important aspects of applications in economics are reviewed,a summary is given in the final section.
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Basic Information:
China Classification Code:O212
Citation Information:
[1]CHEN Jian-bao,DING Jun-jun(Macroeconomics Research Center,Xiamen University,Xiamen 361005,Fujian).A Review of Technologies on Quantile Regression[J].Journal of Statistics and Information,2008,No.90(03):89-96.
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教育部人文社科重点研究基地基金项目《中国地区间收入分配差异与劳动力转移的经济增长效应分析》(07JJD790145);; 教育部人文社科研究基金项目《数据挖掘中关联规则的统计研究和应用》(2006JA910003)