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矩阵函数积分的极大化及两个矩阵特征根分布的渐近展开AI 解读

The noncentral distribution of latent roots arising in several situations in multivariate analysis involves the integration of a hypergeometric function of matrix variates over a group of orthogonal matrices in the real case and that of unitary matrices in the complex case. In this paper the subgroup of the orthogonal group (unitary group) for which the integrand is maximized has been found under mild restrictions. The results of earlier authors (Anderson, Chang, James, Li…

检验指定协方差矩阵的似然比统计量分布AI 解读

The exact null distribution of the likelihood ratio criterion for testing the null hypothesis Σ θ σ0 against the alternative Σ ≠ Σ0 in Np(μ, Σ) has been obtained in a series form and percentage points computed for p θ 2 (1) 10 for α θ 0.005, 0.01, 0.025, 0.05, 0.1 and 0.25 and various degrees of freedom, but only selected tables are presented here.

检验指定协方差矩阵的似然比准则分布AI 解读

The exact null distribution of the likelihood ratio criterion for testing the null hypothesis Σ θ σ0 against the alternative Σ ≠ Σ0 in Np(μ, Σ) has been obtained in a series form and percentage points computed for p θ 2 (1) 10 for α θ 0.005, 0.01, 0.025, 0.05, 0.1 and 0.25 and various degrees of freedom, but only selected tables are presented here.

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多元分析中矩阵最大特征根的分布AI 解读

K. C. SREEDHARAN PILLAI; On the distribution of the largest characteristic root of a matrix in multivariate analysis*, Biometrika, Volume 52, Issue 3-4, 1 Decem

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相对样本均值的极端学生化偏差的分布AI 解读

K. C. S. PILLAI, BENJAMIN P. TIENZO; ON THE DISTRIBUTION OF THE EXTREME STUDENTIZED DEVIATE FROM THE SAMPLE MEAN, Biometrika, Volume 46, Issue 3-4, 1 Decem

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