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Robust Statistics, Data Analysis, and Computer Intensive Methods

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Cover of 'Robust Statistics, Data Analysis, and Computer Intensive Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Bootstrap Variable—Selection and Confidence Sets
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    Chapter 2 Robust Estimation in the Logistic Regression Model
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    Chapter 3 The m out of n Bootstrap and Goodness of Fit Tests with Double Censored Data
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    Chapter 4 What Criterion for a Power Algorithm?
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    Chapter 5 Nonparametric Estimation of Global Functionals of Conditional Quantiles
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    Chapter 6 High Breakdown Point Estimators in Logistic Regression
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    Chapter 7 The Guinea Pig of Multiple Regression
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    Chapter 8 When is a p-Value a Good Measure of Evidence?
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    Chapter 9 Geometric Properties of Principal Curves in the Plane
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    Chapter 10 On Robust Estimation of Variograms in Geostatistics
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    Chapter 11 Advances in Nonparametric Function Estimation
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    Chapter 12 On the Philosophical Foundations of Statistics: Bridges to Huber’s work, and recent results
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    Chapter 13 Data Based Prototyping
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    Chapter 14 Robust Regression with a Categorical Covariable
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    Chapter 15 Robustness in Discriminant Analysis
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    Chapter 16 M-Estimation and Spatial Quantiles
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    Chapter 17 Robust Statistical Methods in Interlaboratory Analytical Studies
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    Chapter 18 Estimating Distributions with a Fixed Number of Modes
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    Chapter 19 Implementing M-Estimators of the Gamma Distribution
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    Chapter 20 Constrained M-Estimation for Regression
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    Chapter 21 Inference for the Direction of the Larger of Two Eigenvectors: The Case of Circular Elongation
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    Chapter 22 High Breakdown Point Designs
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    Chapter 23 On Bayesian Robustness: An Asymptotic Approach
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    Chapter 24 Computational Aspects of Trimmed Single-Link Clustering
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    Chapter 25 Interval Probability on Finite Sample Spaces
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    Chapter 26 On Consistency of Recursive Multivariate M-Estimators in Linear Models
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Title
Robust Statistics, Data Analysis, and Computer Intensive Methods
Published by
Springer, New York, NY, January 1996
DOI 10.1007/978-1-4612-2380-1
ISBNs
978-0-387-94660-3, 978-1-4612-2380-1
Editors

Helmut Rieder

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 9%
Colombia 1 9%
Unknown 9 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Student > Master 2 18%
Student > Doctoral Student 2 18%
Professor 2 18%
Other 1 9%
Other 1 9%
Readers by discipline Count As %
Mathematics 3 27%
Engineering 3 27%
Economics, Econometrics and Finance 1 9%
Computer Science 1 9%
Chemistry 1 9%
Other 2 18%