Recent Advances in Robust Statistics: Theory and Applications

1. Flexible Distributions as an Approach to Robustness: The Skew-t Case
Adelchi Azzalini

2. Determining the Number of Clusters Using Multivariate Ranks
Mohammed Baragilly, Biman Chakraborty

3. Robust and Sparse Estimation of the Inverse Covariance Matrix Using Rank Correlation Measures
Christophe Croux, Viktoria Öllerer

4. Robust Mixture Regression Using Mixture of Different Distributions
Fatma Zehra Doğru, Olcay Arslan

5. Robust Statistical Engineering by Means of Scaled Bregman Distances
Anna-Lena Kißlinger, Wolfgang Stummer

6. SB-Robustness of Estimators
Arnab Kumar Laha, A. C. Pravida Raja

7. Combining Linear Dimension Reduction Subspaces
Eero Liski, Klaus Nordhausen, Hannu Oja, Anne Ruiz-Gazen

8. On the Computation of Symmetrized M-Estimators of Scatter
Jari Miettinen, Klaus Nordhausen, Sara Taskinen, David E. Tyler

9. Mortality and Life Expectancy Forecasting for a Group of Populations in Developed Countries: A Robust Multilevel Functional Data Method
Han Lin Shang

10. Asymptotically Stable Tests with Application to Robust Detection
Georgy Shevlyakov

Keywords: Statistics, Statistics for Business/Economics/Mathematical Finance/Insurance, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law, Statistics and Computing/Statistics Programs, Biostatistics