Recent Advances in Robust Statistics: Theory and Applications

Editors: Claudio Agostinelli, Ayanendranath Basu, Peter Filzmoser, Diganta Mukherjee



Presents a diverse collection of research papers, specifically devoted to the subject of robustnessDiscusses many new applications of and recent advances in robust methods

Explores the applications of robust methods beyond traditional areas

This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and  multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statistical methods.

The aim of the ICORS conference, which is being organized annually since 2001, is to bring together researchers interested in robust statistics, data analysis and related areas. The conference is meant for theoretical and applied statisticians, data analysts from other fields, leading experts, junior researchers and graduate students. The ICORS meetings offer a forum for discussing recent advances and emerging ideas in statistics with a focus on robustness, and encourage informal contacts and discussions among all the participants. They also play an important role in maintaining a cohesive group of international researchers interested in robust statistics and related topics, whose interactions transcend the meetings and endure year round.

Table of contents

Front Matter
Pages i-x

Flexible Distributions as an Approach to Robustness: The Skew-t Case
Pages 1-16

Determining the Number of Clusters Using Multivariate Ranks
Pages 17-33

Robust and Sparse Estimation of the Inverse Covariance Matrix Using Rank Correlation Measures
Pages 35-55

Robust Mixture Regression Using Mixture of Different Distributions
Pages 57-79

Robust Statistical Engineering by Means of Scaled Bregman Distances
Pages 81-113

SB-Robustness of Estimators
Pages 115-130

Combining Linear Dimension Reduction Subspaces
Pages 131-149

On the Computation of Symmetrized M-Estimators of Scatter
Pages 151-167

Mortality and Life Expectancy Forecasting for a Group of Populations in Developed Countries: A Robust Multilevel Functional Data Method
Pages 169-184

Asymptotically Stable Tests with Application to Robust Detection
Pages 185-199

Back Matter
Pages 201-201

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