Recent Advances in Robust Statistics: Theory and Applications

Description

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. 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