Robustness and Complex Data Structures (eBook)

Festschrift in Honour of Ursula Gather
eBook Download: PDF
2014 | 2013
X, 379 Seiten
Springer Berlin (Verlag)
978-3-642-35494-6 (ISBN)

Lese- und Medienproben

Robustness and Complex Data Structures -
Systemvoraussetzungen
96,29 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
?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.  

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

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

​Part I Univariate and Multivariate Robust Methods: Multivariate Median (Hannu Oja).- Depth Statistics (Karl Mosler).- Multivariate Extremes: A Conditional Quantile Approach (Marie-Françoise Barme-Delcroix).- High-Breakdown Estimators of Multivariate Location and Scatter (Peter Rousseeuw and Mia Hubert).- Upper and Lower Bounds for Breakdown Points (Christine H. Müller).- The Concept of α-outliers in Structured Data Situations (Sonja Kuhnt and André Rehage).- Multivariate OutlierIidentification Based on Robust Estimators of Location and Scatter (Claudia Becker, Steffen Liebscher and Thomas Kirschstein).- Robustness for Compositional Data (Peter Filzmoser and Karel Hron).- Part II Regression and Time Series Analysis:  Least Squares Estimation in High Dimensional Sparse Heteroscedastic Models (Holger Dette and Jens Wagener).- Bayesian Smoothing, Shrinkage and Variable Selection in Hazard Regression (Susanne Konrath, Ludwig Fahrmeir and Thomas Kneib).- Robust Change Point Analysis (Marie Hušková).- Robust Signal Extraction From Time Series in Real Time (Matthias Borowski, Roland Fried and Michael Imhoff).- Robustness in Time Series: Robust Frequency Domain Analysis (Bernhard Spangl and Rudolf Dutter).- Robustness in Statistical Forecasting (Yuriy Kharin).- Finding Outliers in Linear and Nonlinear Time Series (Pedro Galeano and Daniel Peña).- Part III Complex Data Structures: Qualitative Robustness of Bootstrap Approximations for Kernel Based Methods (Andreas Christmann, Matías Salibián-Barrera and Stefan Van Aels).- Some Machine Learning Approaches to the Analysis of Temporal Data (Katharina Morik).- Correlation, Tail Dependence and Diversification (Dietmar Pfeifer).- Evidence for Alternative Hypotheses (Stephan Morgenthaler and Robert G. Staudte).- Concepts and a Case Study for a Flexible Class of Graphical Markov Models (NannyWermuth and David R. Cox).- Data Mining in Pharmacoepidemiological Databases (Marc Suling, Robert Weber and Iris Pigeot).- Meta-Analysis of Trials with Binary Outcomes (JürgenWellmann).

Erscheint lt. Verlag 8.7.2014
Zusatzinfo X, 379 p.
Verlagsort Berlin
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Technik
Schlagworte Complex Data Analysis • Nonparametric regression • Robust Statistics • Time Series Analysis
ISBN-10 3-642-35494-7 / 3642354947
ISBN-13 978-3-642-35494-6 / 9783642354946
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 12,7 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Zusätzliches Feature: Online Lesen
Dieses eBook können Sie zusätzlich zum Download auch online im Webbrowser lesen.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich