Estimation and Testing Under Sparsity

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  • Estimation and Testing Under Sparsity Book Detail

  • Author : Sara van de Geer
  • Release Date : 2016-06-28
  • Publisher : Springer
  • Genre : Mathematics
  • Pages : 278
  • ISBN 13 : 3319327747
  • File Size : 89,89 MB

Estimation and Testing Under Sparsity by Sara van de Geer PDF Summary

Book Description: 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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