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Estimation and Testing Under Sparsity
Sara van de Geer
其他書名
École d'Été de Probabilités de Saint-Flour XLV – 2015
出版Springer, 2016-06-28
主題Mathematics / Probability & Statistics / GeneralComputers / Mathematical & Statistical SoftwareMathematics / Probability & Statistics / Stochastic ProcessesMathematics / Discrete Mathematics
ISBN33193277479783319327747
URLhttp://books.google.com.hk/books?id=WQWPDAAAQBAJ&hl=&source=gbs_api
EBookSAMPLE
註釋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.