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线性回归模型中的最小距离估计AI 解读

This paper discusses a class of minimum distance Cramer-Von Mises type estimators of the slope parameter in a linear regression model. These estimators are obtained by minimizing an integral of squared difference between weighted empiricals of the residuals and their expectations with respect to a large class of integrating measures. The estimator corresponding to the weights proportional to the design variable is shown to be asymptotically efficient within the class at a…

随机右删失数据的回归分析AI 解读

This paper proposes a new estimator of the parameter vector in a linear regression model when the observations are randomly censored on the right and when the error distribution is unknown. This estimator is explicitly defined and easily computable. The paper contains sufficient conditions under which this estimator is mean square consistent and asymptotically normal. A numerical example is given.