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Handbook of Computational Statistics : Concepts and Methods

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Cover of 'Handbook of Computational Statistics : Concepts and Methods'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 How Computational Statistics Became the Backbone of Modern Data Science
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    Chapter 2 Basic Computational Algorithms
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    Chapter 3 Random Number Generation
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    Chapter 4 Markov Chain Monte Carlo Technology
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    Chapter 5 Numerical Linear Algebra
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    Chapter 6 The EM Algorithm
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    Chapter 7 Stochastic Optimization
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    Chapter 8 Transforms in Statistics
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    Chapter 9 Parallel Computing Techniques
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    Chapter 10 Statistical Databases
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    Chapter 11 Discovering and Visualizing Relations in High Dimensional Data
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    Chapter 12 Interactive and Dynamic Graphics
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    Chapter 13 The Grammar of Graphics
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    Chapter 14 Statistical User Interfaces
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    Chapter 15 Object Oriented Computing
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    Chapter 16 Model Selection
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    Chapter 17 Bootstrap and Resampling
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    Chapter 18 Design and Analysis of Monte Carlo Experiments
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    Chapter 19 Multivariate Density Estimation and Visualization
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    Chapter 20 Smoothing: Local Regression Techniques
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    Chapter 21 Semiparametric Models
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    Chapter 22 Dimension Reduction Methods
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    Chapter 23 (Non) Linear Regression Modeling
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    Chapter 24 Generalized Linear Models
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    Chapter 25 Robust Statistics
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    Chapter 26 Bayesian Computational Methods
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    Chapter 27 Computational Methods in Survival Analysis
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    Chapter 28 Data and Knowledge Mining
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    Chapter 29 Recursive Partitioning and Tree-based Methods
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    Chapter 30 Support Vector Machines
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    Chapter 31 Learning Under Non-stationarity: Covariate Shift Adaptation by Importance Weighting
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    Chapter 32 Saddlepoint Approximations: A Review and Some New Applications
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    Chapter 33 Bagging, Boosting and Ensemble Methods
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    Chapter 34 Heavy-Tailed Distributions in VaR Calculations
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    Chapter 35 Econometrics
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    Chapter 36 Statistical and Computational Geometry of Biomolecular Structure
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    Chapter 37 Functional Magnetic Resonance Imaging
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    Chapter 38 Network Intrusion Detection
Attention for Chapter 34: Heavy-Tailed Distributions in VaR Calculations
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Chapter title
Heavy-Tailed Distributions in VaR Calculations
Chapter number 34
Book title
Handbook of Computational Statistics
Published by
Springer Berlin Heidelberg, November 2015
DOI 10.1007/978-3-642-21551-3_34
Book ISBNs
978-3-64-221550-6, 978-3-64-221551-3
Authors

Adam Misiorek, Rafał Weron

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 25%
Student > Doctoral Student 1 25%
Unknown 2 50%
Readers by discipline Count As %
Mathematics 1 25%
Engineering 1 25%
Unknown 2 50%