雙截尾Tobit模型中的隨機(jī)加權(quán)逼近方法
發(fā)布時(shí)間:2021-12-11 23:54
本文研究雙截尾刪失回歸模型中參數(shù)的隨機(jī)加權(quán)估計(jì)(RWE),獲得了RWE的統(tǒng)計(jì)漸近性質(zhì),如相合性和漸近分布.本文證明了RWE在給定樣本下的條件漸近分布與參數(shù)的最小絕對(duì)偏差(LAD)估計(jì)的漸近分布是一樣的,則可以利用RWE的條件分布去逼近回歸參數(shù)的LAD估計(jì)的分布,從而避免冗余參數(shù)的估計(jì),如誤差項(xiàng)的密度函數(shù).另外,本文也提出了一個(gè)M檢驗(yàn)統(tǒng)計(jì)量和隨機(jī)加權(quán)M檢驗(yàn)統(tǒng)計(jì)量(RWM)來檢驗(yàn)參數(shù)的線性假設(shè)問題,建立了該檢驗(yàn)的統(tǒng)計(jì)性質(zhì).數(shù)值模擬和實(shí)際數(shù)據(jù)分析結(jié)果表明所提方法是可行的.
【文章來源】:中國科學(xué):數(shù)學(xué). 2018,48(07)北大核心CSCD
【文章頁數(shù)】:14 頁
【參考文獻(xiàn)】:
期刊論文
[1]雙尾Tobit模型中LAD估計(jì)的漸近正態(tài)性[J]. 王曉鳳,王占鋒,吳耀華. 中國科學(xué)技術(shù)大學(xué)學(xué)報(bào). 2014(09)
[2]Approximation by randomly weighting method in censored regression model[J]. WANG ZhanFeng, WU YaoHua & ZHAO LinCheng Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China. Science in China(Series A:Mathematics). 2009(03)
[3]Strong convergence of LAD estimates in a censored regression model[J]. FANG Yixin, JIN Man & ZHAO Lincheng Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China. Science in China,Ser.A. 2005(02)
本文編號(hào):3535625
【文章來源】:中國科學(xué):數(shù)學(xué). 2018,48(07)北大核心CSCD
【文章頁數(shù)】:14 頁
【參考文獻(xiàn)】:
期刊論文
[1]雙尾Tobit模型中LAD估計(jì)的漸近正態(tài)性[J]. 王曉鳳,王占鋒,吳耀華. 中國科學(xué)技術(shù)大學(xué)學(xué)報(bào). 2014(09)
[2]Approximation by randomly weighting method in censored regression model[J]. WANG ZhanFeng, WU YaoHua & ZHAO LinCheng Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China. Science in China(Series A:Mathematics). 2009(03)
[3]Strong convergence of LAD estimates in a censored regression model[J]. FANG Yixin, JIN Man & ZHAO Lincheng Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China. Science in China,Ser.A. 2005(02)
本文編號(hào):3535625
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