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Více informací o knize Estimation and Testing Under Sparsity

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• Anotace
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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Mathematics Probability & statistics

• Plný název: Estimation and Testing Under Sparsity
• Podnázev: École d'Été de Probabilités de Saint-Flour XLV - 2015
• Autor: Sara van de Geer
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 274
• EAN: 9783319327730
• ISBN: 3319327739
• ID: 02961495
• Nakladatelství: Springer International Publishing AG
• Hmotnost: 436 g
• Rozměry: 234 × 154 × 21 mm
• Datum vydání: 29. June 2016

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