Estimation and Testing Under Sparsity: École d'Été de Probabilités de Saint-Flour XLV - 2015 (Paperback) (ISBN-13: 9783319327730)

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.

Author: Sara Van de Geer
ISBN-10: 3319327739
ISBN-13: 9783319327730
Publisher: Springer
Language: English
Published: 06/29/2016
Pages: 274
Format: Paperback
Weight: 0.91lbs
Size: 9.21h x 6.14w x 0.61d