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基于正态但相依观测的最大似然估计量的渐近正态性AI 解读

In this article we aim to establish intuitively appealing and verifiable conditions for the first-order efficiency and asymptotic normality of ML estimators in a multi-parameter framework, assuming joint normality but neither the independence nor the identical distribution of the observations. We present five theorems (and a large number of lemmas and propositions), each being a special case of its predecessor.

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对称性、0–1 矩阵与雅可比矩阵：综述AI 解读

In this paper we bring together those properties of the Kronecker product, the vec operator, and 0-1 matrices which in our view are of interest to researchers and students in econometrics and statistics. The treatment of Kronecker products and the vec operator is fairly exhaustive; the treatment of 0–1 matrices is selective. In particular we study the “commutation” matrix K (defined implicitly by K vec A = vec A′ for any matrix A of the appropriate order), the idempotent…

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特征值与特征向量的求导AI 解读

Let X 0 be a square matrix (complex or otherwise) and u 0 a (normalized) eigenvector associated with an eigenvalue λ o of X 0 , so that the triple ( X 0 , u 0 , λ 0 ) satisfies the equations Xu = λ u , . We investigate the conditions under which unique differentiable functions λ( X ) and u ( X ) exist in a neighborhood of X 0 satisfying λ( X 0 ) = λ O , u ( X 0 ) = u 0 , X u = λ u , and . We obtain the first and second derivatives of λ( X ) and the first derivative of u ( X…

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交换矩阵：若干性质与应用AI 解读

The commutation matrix $K$ is defined as a square matrix containing only zeroes and ones. Its main properties are that it transforms vecA into vecA', and that it reverses the order of a Kronecker product. An analytic expression for $K$ is given and many further properties are derived. Subsequently, these properties are applied to some problems connected with the normal distribution. The expectation is derived of $\varepsilon' A\varepsilon\cdot\varepsilon' B\varepsilon\cdot\varepsilon'C\varepsilon$…

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