双截尾Tobit模型中的随机加权逼近方法
发布时间：2021-12-11 23:54
本文研究双截尾删失回归模型中参数的随机加权估计（RWE）,获得了RWE的统计渐近性质,如相合性和渐近分布.本文证明了RWE在给定样本下的条件渐近分布与参数的最小绝对偏差（LAD）估计的渐近分布是一样的,则可以利用RWE的条件分布去逼近回归参数的LAD估计的分布,从而避免冗余参数的估计,如误差项的密度函数.另外,本文也提出了一个M检验统计量和随机加权M检验统计量（RWM）来检验参数的线性假设问题,建立了该检验的统计性质.数值模拟和实际数据分析结果表明所提方法是可行的.
【文章来源】：中国科学:数学. 2018,48(07)北大核心CSCD
【文章页数】：14 页
【参考文献】：
期刊论文
[1]双尾Tobit模型中LAD估计的渐近正态性[J]. 王晓凤,王占锋,吴耀华. 中国科学技术大学学报. 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)
本文编号：3535625
【文章来源】：中国科学:数学. 2018,48(07)北大核心CSCD
【文章页数】：14 页
【参考文献】：
期刊论文
[1]双尾Tobit模型中LAD估计的渐近正态性[J]. 王晓凤,王占锋,吴耀华. 中国科学技术大学学报. 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)
本文编号：3535625
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