Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach...
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents ...
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach...
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents ...
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...
Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing r...
Formulated through discussions with van Zwet himself, this volume is a collection of papers that truly reflects the range of the subject's research, and which covers themes ranging from asymptotic theory to probability and second-order approximations.
Formulated through discussions with van Zwet himself, this volume is a collection of papers that truly reflects the range of the subject's research, a...
