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最优线性递归估计AI 解读

This article presents a matrix formulation of recursive forms for best linear unbiased estimators [Xcirc]N of the parameter vector x in the linear model yi=hix+ei, i = 1,2, ···, N when the observation vectors yi are correlated. If data are collected in sequence one can formulate recursive forms of the estimator [Xcirc]N so that it is not necessary to store all the previous data but only previous estimates and current data. This requires less storage space to obtain best…

最优线性递推估计AI 解读

This article presents a matrix formulation of recursive forms for best linear unbiased estimators [Xcirc]N of the parameter vector x in the linear model yi=hix+ei, i = 1,2, ···, N when the observation vectors yi are correlated. If data are collected in sequence one can formulate recursive forms of the estimator [Xcirc]N so that it is not necessary to store all the previous data but only previous estimates and current data. This requires less storage space to obtain best…

正规或遍历转移矩阵的不动点概率向量AI 解读

A simple form for the fixed point probability row vector of regular or ergodic transition matrices is developed using some of the theory of generalized matrix inversion, together with the well known existence and uniqueness of a fixed point probability row vector. The forms for both the regular and ergodic case are identical and afford the easy calculation of the fixed point without calculating powers of the transition matrix or considering the usual convergence methods.

正则或遍历转移矩阵的不动点概率向量AI 解读

A simple form for the fixed point probability row vector of regular or ergodic transition matrices is developed using some of the theory of generalized matrix inversion, together with the well known existence and uniqueness of a fixed point probability row vector. The forms for both the regular and ergodic case are identical and afford the easy calculation of the fixed point without calculating powers of the transition matrix or considering the usual convergence methods.

高斯—马尔可夫定理的一个推广AI 解读

This paper contains a generalization of the Gauss Markov Theorem based on the properties of the generalized inverse of a matrix as defined by Penrose. A minimum variance vector estimate of a parameter vector x is given for the linear model of less than full rank. Since linear unbiased estimates may not always exist for this case the unbiased constraint is replaced by the more general constraint that the norm is minimized.

生成样本协方差矩阵的数值程序AI 解读

U SE of random numbers, especially in Monte Carlo procedure, is an established practice in most large computing centers. T. E. Hull and A. R. Dobell [1 ] in their paper Random Number Generators, give a relative large number of references to early as well as recent (up to 1962) work on random numbers. J. M. Hammersley and D. C. Handscomb [2] have written a book entitled Monte Carlo Methods, that contains not only a discussion on generating random numbers, but also several…