概括线性模型(GLM ) 基于有在随机的审查的情况中的不完全的信息的观察数据被定义。在给定的条件下面,关于模型的参数向量贝它的可能性方程上的解决方案的存在和唯一被讨论,并且 beta_n 被证明的最大的可能性评估者(MLE ) 的一致性和 asymptotic 规度。
The generalized linear model(GLM) based on the observed data with incomplete information in the case of random censorship is defined. Under the given conditions, the existence and uniqueness of the solution on the likelihood equations with respect to the parameter vector β of the model are discussed, and the consistency and asymptotic normality of the maximum likelihood estimator(MLE) βn^-, are proved.