Estimation and Testing Under Sparsity

Estimation and Testing Under Sparsity
Author :
Publisher : Springer
Total Pages : 278
Release :
ISBN-10 : 9783319327747
ISBN-13 : 3319327747
Rating : 4/5 (747 Downloads)

Book Synopsis Estimation and Testing Under Sparsity by : Sara van de Geer

Download or read book Estimation and Testing Under Sparsity written by Sara van de Geer and published by Springer. This book was released on 2016-06-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers. It also provides a semi-parametric approach to establishing confidence intervals and tests. Sparsity-inducing methods have proven to be very useful in the analysis of high-dimensional data. Examples include the Lasso and group Lasso methods, and the least squares method with other norm-penalties, such as the nuclear norm. The illustrations provided include generalized linear models, density estimation, matrix completion and sparse principal components. Each chapter ends with a problem section. The book can be used as a textbook for a graduate or PhD course.


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