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Introduction to high-dimensional statistics

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such...

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Bibliographic Details
Main Author: Giraud, Christophe
Format: eBook
Language:English
Published: Boca Raton CRC Press, Taylor & Francis Group 2015
Series:Monographs on statistics & applied probability
Subjects:
Dimensional Analysis / Fast
Dimensional Analysis / Http://id.loc.gov/authorities/subjects/sh85038036
Big Data / Fast
Big Data / Http://id.loc.gov/authorities/subjects/sh2012003227
Hochdimensionale Daten / Gnd / Http://d-nb.info/gnd/7862975-5
Données Volumineuses
Multivariate Analysis / Http://id.loc.gov/authorities/subjects/sh85088390
Mathematische Modellierung / Gnd / Http://d-nb.info/gnd/7651795-0
Statistik / Gnd
Mathematics / Probability & Statistics / General / Bisacsh
Multivariate Analysis / Fast
Datenanalyse / Gnd
Inferenzstatistik / Gnd
Analyse Multivariée
Analyse Dimensionnelle
Mathematics / Applied / Bisacsh
Statistics / Http://id.loc.gov/authorities/subjects/sh85127580
Statistics / Fast
Statistics / Aat
Statistique
Boosting / Gnd / Http://d-nb.info/gnd/4839853-6
Lasso-methode / Gnd / Http://d-nb.info/gnd/7750854-3
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Includes bibliographical references and index
  • Chapter 1: Introduction
  • Chapter 2: Model Selection
  • Chapter 3: Aggregation of Estimators
  • Chapter 4: Convex Criteria
  • Chapter 5: Estimator Selection
  • Chapter 6: Multivariate Regression
  • Chapter 7: Graphical Models
  • Chapter 8: Multiple Testing
  • Chapter 9: Supervised Classification

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