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Informationen zum Autor Jianfeng Yao has rich research experience in random matrix theory and its applications to high-dimensional statistics. In recent years! he has published many authoritative papers in these areas and organised several international workshops on related topics. Shurong Zheng is author of several influential results in random matrix theory including a widely used central limit theorem for eigenvalue statistics of a random Fisher matrix. She has also developed important applications of the inference theory presented in the book to real-life high-dimensional statistics. Zhidong Bai is a world-leading expert in random matrix theory and high-dimensional statistics. He has published over 200 research papers and several specialized monographs! including Spectral Analysis of Large Dimensional Random Matrices (with J. W. Silverstein)! for which he won the Natural Science Award of China (Second Class). Klappentext Written by leading experts in the field! this book presents the most recent developments in the use of random matrix theory in high-dimensional statistics. Zusammenfassung High-dimensional statistical methods are at the heart of the new era of big data analytics. This book! written by leading experts! is highly recommended for anyone who wants to make serious use of these modern statistical tools. Inhaltsverzeichnis 1. Introduction; 2. Limiting spectral distributions; 3. CLT for linear spectral statistics; 4. The generalised variance and multiple correlation coefficient; 5. The T2-statistic; 6. Classification of data; 7. Testing the general linear hypothesis; 8. Testing independence of sets of variates; 9. Testing hypotheses of equality of covariance matrices; 10. Estimation of the population spectral distribution; 11. Large-dimensional spiked population models; 12. Efficient optimisation of a large financial portfolio.
