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Robustness and Complex Data Structures

Festschrift in Honour of Ursula Gather

  • Book
  • © 2013

Overview

Editors:
  1. Claudia Becker

    1. Halle-Wittenberg, Faculty of Law and Economics, Martin-Luther-University, Halle, Germany

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  2. Roland Fried

    1. Faculty of Statistics, TU Dortmund University, Dortmund, Germany

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  3. Sonja Kuhnt

    1. Faculty of Statistics, TU Dortmund University, Dortmund, Germany

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  • Concise presentations of the relevant theory for the basic as well as up-to-date topics

  • Complex data structures beyond the pure treatment of robust methods

  • Robust methods for all fields of statistical analysis All contributions contain pointers to relevant algorithms and packages

  • Includes supplementary material: sn.pub/extras

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Table of contents (22 chapters)

  1. Front Matter

    Pages I-X
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  2. Univariate and Multivariate Robust Methods

    1. Front Matter

      Pages 1-1
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    2. Multivariate Median

      • Hannu Oja
      Pages 3-15

    3. Depth Statistics

      • Karl Mosler
      Pages 17-34

    4. Multivariate Extremes: A Conditional Quantile Approach

      • Marie-Françoise Barme-Delcroix
      Pages 35-48

    5. High-Breakdown Estimators of Multivariate Location and Scatter

      • Peter Rousseeuw, Mia Hubert
      Pages 49-66

    6. Upper and Lower Bounds for Breakdown Points

      • Christine H. Müller
      Pages 67-84

    7. The Concept of α-Outliers in Structured Data Situations

      • Sonja Kuhnt, André Rehage
      Pages 85-101

    8. Multivariate Outlier Identification Based on Robust Estimators of Location and Scatter

      • Claudia Becker, Steffen Liebscher, Thomas Kirschstein
      Pages 103-115

    9. Robustness for Compositional Data

      • Peter Filzmoser, Karel Hron
      Pages 117-131

  3. Regression and Time Series Analysis

    1. Front Matter

      Pages 133-133
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    2. Least Squares Estimation in High Dimensional Sparse Heteroscedastic Models

      • Holger Dette, Jens Wagener
      Pages 135-147

    3. Bayesian Smoothing, Shrinkage and Variable Selection in Hazard Regression

      • Susanne Konrath, Ludwig Fahrmeir, Thomas Kneib
      Pages 149-170

    4. Robust Change Point Analysis

      • Marie HuÅ¡ková
      Pages 171-190

    5. Robust Signal Extraction from Time Series in Real Time

      • Matthias Borowski, Roland Fried, Michael Imhoff
      Pages 191-206

    6. Robustness in Time Series: Robust Frequency Domain Analysis

      • Bernhard Spangl, Rudolf Dutter
      Pages 207-223

    7. Robustness in Statistical Forecasting

      • Yuriy Kharin
      Pages 225-242

    8. Finding Outliers in Linear and Nonlinear Time Series

      • Pedro Galeano, Daniel Peña
      Pages 243-260

  4. Complex Data Structures

    1. Front Matter

      Pages 261-261
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    2. Qualitative Robustness of Bootstrap Approximations for Kernel Based Methods

      • Andreas Christmann, Matías Salibián-Barrera, Stefan Van Aelst
      Pages 263-278
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Keywords

About this book

​This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.  

Editors and Affiliations

  • Halle-Wittenberg, Faculty of Law and Economics, Martin-Luther-University, Halle, Germany

    Claudia Becker

  • Faculty of Statistics, TU Dortmund University, Dortmund, Germany

    Roland Fried, Sonja Kuhnt

About the editors

Prof. Dr. Claudia Becker is a Professor of Statistics at the Faculty of Law and Economics, Martin-Luther University Halle-Wittenberg. Her research priorities are robust statistical methods; robust statistical methods for dimension reduction in complex data structures; and statistical methods for regional economics to assess complex situations and relationships through interviews, with a particular focus on innovation and entrepreneurship research

Prof. Dr. Roland Fried has been a Professor of Statistics in Biosciences at the Faculty of Statistics, Dortmund University, since 2006. His research focuses on biostatistics; modeling spatial and temporal data; online monitoring; robust signal extraction and structural break detection, and efficient statistical computational algorithms

PD Dr. Sonja Kuhnt has held a temporary professorship at the Institute for Mathematical Statistics with Applications in Industry, Faculty for Statistics, TU Dortmund University, since 2008. Her present research fields are robust methods for categorical data and graphical models; computer algebra in statistics; offline planning of industrial processes; and acquisition of information in logistics

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