【摘 要】
：
Suppose that in the regression modelYi =x′iβ + ei,i =1,2,…,n,(1)only Yi+ =YiI(Yi ≥ 0) and xi are observable,where I(·) denotes the indicator function of a set.In other words,the model under considerat
【机 构】
：
University of Science and Technology of China, China
【出 处】
：
The 15th International Conference of Forum for Interdiscipli
论文部分内容阅读
Suppose that in the regression modelYi =x′iβ + ei,i =1,2,…,n,(1)only Yi+ =YiI(Yi ≥ 0) and xi are observable,where I(·) denotes the indicator function of a set.In other words,the model under consideration is the following one with the non-negativity constraint on the dependent variables:Yi+ =(x′i+ei)+,i =1,...,n,(2)where β is the unknown p-vectors of regression parameters,eis are random errors.Here we distinguish two cases.In the first case we assume that {xi} is a sequence of known design points,and {ei} is an iid.sequence,such that med(ei) =0 for all i.In another case we assume that {(xi,ei)} is a sequence of iid.random variables,and med(ei|xi) =0 for all i.
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