论文检索

不完整多项分布数据的极大似然估计AI 解读

When sampling from a multinomial population, it may happen either by chance or by design that some of the observations are only partially classified. In this article the amount of information in the partially classified observation is evaluated, and maximum likelihood estimators are obtained using both completely classified and partially classified data. In general an iterative solution is required, but special cases are identified in which the solution is obtained in closed…

存在缺失观测时多元正态分布的参数估计AI 解读

In this paper a method is developed for estimating the parameters in the multivariate normal distribution in which the missing observavations are not restricted to follow certain patterns as in most previous papers. The large sample properties of the estimators are discussed. Equivalence with maximum likelihood estimators has been established for a subclass of problems. The results of some simulation studies are provided to support the theoretical development.

参数受不等式约束的二次回归AI 解读

A method is given here for fitting a quadratic subject to restrictions on the location of the extreme point which is conceptually somewhat different from that proposed by Cunia [1]. The solution is presented as a special case of the general quadratic programming problem, that is, minimizing a quadratic function subject to restrictions on the variables.

参数具有不等式约束的二次回归AI 解读

A method is given here for fitting a quadratic subject to restrictions on the location of the extreme point which is conceptually somewhat different from that proposed by Cunia [1]. The solution is presented as a special case of the general quadratic programming problem, that is, minimizing a quadratic function subject to restrictions on the variables.