High-Dimensional Data Analysis (V2)

Over the last few years, significant developments have been taking place in high-dimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. In particular, substantial advances have been made in the areas of feature selection, covariance estimation, classification and regression. This book intends to examine important issues arising from high-dimensional data analysis to explore key ideas for statistical inference and prediction.
It is structured around topics on multiple hypothesis testing, feature selection, regression, classification, dimension reduction, as well as applications in survival analysis and biomedical research.
The book will appeal to graduate students and new researchers interested in the plethora of opportunities available in high-dimensional data analysis.

Product details

• Authors: Tony Cai & Xiaotong Shen
• Assisted by: T Tony Cai (Editor), T. Tony Cai (Editor), Xiaotong Shen (Editor), Tony Cai (Editor), Xiaotong Shen (Editor)
• Publisher: Wsp/other Publr
• Languages: English
• Product format: Hardback
• Released: 15.12.2010
• EAN: 9789814324854
• ISBN: 978-981-4324-85-4
• No. of pages: 320
• Dimensions: 157 mm x 235 mm x 22 mm
• Weight: 616 g
• Series: Frontiers of Statistics
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics