中文摘要：

multivariate 线性 errors-in-variables 模型 regressors 什么时候在在 Rubin (1976 ) 的意义的随机是失踪的，在这份报纸被考虑。为 0 在这建模的一个参数的一个抑制实验可能性的信心区域被建议，它被基于反的概率把相应于加权的摆平的直角的距离的 20 个函数与 0 的一个抑制区域相结合构造。在真参数的实验木头可能性的比率收敛到标准 chi 平方分发，这被显示出。模拟证明建议信心区域的范围率接近名字的水平，信心间隔的长度是比反的概率的正常近似的那些狭窄的在大多数情况中的加权的调整最不方形的评估者。一个真实例子被学习，结果支持理论和模拟结论。

英文摘要：

The multivariate linear errors-in-variables model when the regressors are missing at random in the sense of Rubin （1976） is considered in this paper. A constrained empirical likelihood confidence region for a parameter β0 in this model is proposed, which is constructed by combining the score function corresponding to the weighted squared orthogonal distance based on inverse probability with a constrained region of β0. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. Simulations show that the coverage rate of the proposed confidence region is closer to the nominal level and the length of confidence interval is narrower than those of the normal approximation of inverse probability weighted adjusted least square estimator in most cases. A real example is studied and the result supports the theory and simulation＇s conclusion.