Large sample theory of maximum likelihood estimation 极大似然估计值的大样本理论
On the basis of large sample theory, how to test non-inferiority ( and equivalence) between two diagnostic procedures in paired-sample ordinal data is studied. 利用大样本理论研究了具有成对有序观测数据诊断过程的比较问题。
The main stream in these studies basically using a large sample surveys, revealed the content of the implicit theory, which was comprehensive, but not profound. 这些研究基本采用大样本调查获得,对公众的创造力内隐观内容揭示得全面,但是不深刻。
When tagging a large number of categories with high price of the sample, combined with the incremental learning theory is an effective way to solve the problem. 当获得大量带有类别标注的样本代价较高时,与增量学习理论结合是解决问题的有效途径。