论文检索

积分比值的一个实用不等式及其极大似然估计应用AI 解读

A generalization of a well-known covariance inequality is proved and is used to furnish sufficient conditions for the strict concavity of the log-likelihood of an observable random variable Y as a function of a real parameter θ that governs the distribution of an unobservable random variable X on which the distribution of Y depends in a known way.

摘要暂缺

构造给定类中全部最小同时置信集及其MANOVA应用AI 解读

A method is presented for the construction of all families of smallest simultaneous confidence sets (SCS) in a given class, for a family $\{\psi_i(\gamma)\}$ of parametric functions of the parameter of interest $\gamma = \gamma(\theta)$. The method is applied to the MANOVA problem (in its canonical form) of inference about $M = EX$, where $X$ is $q \times p$ and has rows that are independently multivariate normal with common covariance matrix $\Sigma$. Let $S$ be the usual…