Multivariate statistical analysis : a high-dimensional approach
Multivariate statistical analysis : a high-dimensional approach
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多元统计分析：一种高维方法
DOI：
10.1007/978-94-015-9468-4
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发表时间：
2000
影响因子：
1.6
通讯作者：
V. Serdobolʹskiĭ
中科院分区：
文献类型：
--
作者：
V. Serdobolʹskiĭ
序言。导论. 1.大型Wishart矩阵的谱性质。2.大样本协方差矩阵的预解式和谱函数。3.大合并样本协方差矩阵的预解式和谱函数。4.质量函数的正态估计。5.高维逆协方差矩阵的估计。6.正态均值的ε-支配的广义收缩估计。7.高维期望向量的改进估计。8.具有大量随机预测的线性回归的二次风险。9.正态总体协方差阵重合的线性判别分析。10.无歧视的人口质量。11.自变量个数递增的判别分析理论。结论.参考资料。指数.
Preface. Introduction. 1. Spectral Properties of Large Wishart Matrices. 2. Resolvents and Spectral Functions of Large Sample Covariance Matrices. 3. Resolvents and Spectral Functions of Large Pooled Sample Covariance Matrices. 4. Normal Evaluation of Quality Functions. 5. Estimation of High-Dimensional Inverse Covariance Matrices. 6. Epsilon-Dominating Component-Wise Shrinkage Estimators of Normal Mean. 7. Improved Estimators of High-Dimensional Expectation Vectors. 8. Quadratic Risk of Linear Regression with a Large Number of Random Predictors. 9. Linear Discriminant Analysis of Normal Populations with Coinciding Covariance Matrices. 10. Population Free Quality of Discrimination. 11. Theory of Discriminant Analysis of the Increasing Number of Independent Variables. Conclusions. References. Index.