Title	Statistical Data Analysis Based on the L1-Norm and Related Methods [electronic resource] / edited by Yadolah Dodge
Imprint	Basel : Birkhรคuser Basel : Imprint: Birkhรคuser, 2002
Connect to	http://dx.doi.org/10.1007/978-3-0348-8201-9
Descript	XII, 456 p. online resource

This volume contains a selection of invited papers, presented to the fourth Inยญ Statistical Analysis Based on the L1-Norm and Related ternational Conference on Methods, held in Neuchatel, Switzerland, from August 4-9, 2002. Organized jointly by the University of Illinois at Chicago (Gib Bassett), the Rutgers University (Regina Liu and Yehuda Vardi) and the University of Neuchatel (Yadolah Dodge), the conference brought together experts whose research deals with theory and apยญ plications involving the L1-Norm. The conference included invited and contributed talks as well as a tutorial on Quantile Regression. This volume includes 36 refereed invited papers under seven headings. Part one deals with Quantiles in all their forms and shapes. It includes papers on quantile functions in non-parametric multivariate analysis, and empirical applications of quantile regression. Much of the development in this direction follows from the fundamental paper by Koenker and Bassett in 1978. Financial and Time Series A nalysis follows the section on quantiles. Part three concerns Estimation, Testing and Characterization. Part four, Deep in the Data, deals with issues related to data depth. Part five addresses Classification questions. The problem of Density Estimation and Image Processing is discussed in Part six, and finally Part seven presents two environmental applications. The contributions represent clear evidence of important research involving theoยญ retical issues and applications associated with the L1-Norm. It is my hope that the articles contained in this volume and its predecessors, published in 1987, 1992, and 1997, will stimulate interest among researchers

Quantile Functions and Spread for Multivariate Distributions -- A New Definition of Multivariate M-quantiles -- A Depth Function and a Scale Curve Based on Spatial Quantiles -- Sample Quantiles for Locally Dependent Processes -- What are the Limiting Distributions of Quantile Estimators? -- New Selection Indices for University Admissions: A Quantile Approach -- Exploring Transition Data Through Quantile Regression Methods: An Application to U.S. Unemployment Duration -- How to be Pessimistic: Choquet Risk and Portfolio Optimization -- Expected Shortfall and Beyond -- Credit Scoring Using Binary Quantile Regression -- Prediction of 0โ1-Events for Short- and Long-memory Time Series -- Nonparametric Quantile Regression with Applications to Financial Time Series -- An Algorithm for Optimal Bandwidth Selection for Smooth Nonparametric Quantile Estimation -- Orthogonal L1-norm Estimation -- L1-Derivatives, Score Functions and Tests -- Optimal Bias Robust M-estimates of Regression -- Robust Bootstrap for S-estimators of Multivariate Regression -- M-tests for Detection of Structural Changes in Regression -- Change Point Detection Based on Empirical Quantiles -- A Class of Probability Metrics and its Statistical Applications -- Whose Hare and Whose Tortoise -- Sign and Rank Covariance Matrices: Statistical Properties and Application to Principal Components Analysis -- Multivariate Signed Ranks: Randiesโ Interdirections or Tylerโs Angles? -- L1-Depth, Depth Relative to a Model, and Robust Regression -- Perturbation Properties of Depth Regions -- Multivariate Trimmed Means Based on Data Depth -- Graphs, L1-Metrics and Clustering -- Classification Based on the Support Vector Machine and on Regression Depth -- A Robust Clustering Method and Visualization Tool Based On Data Depth -- The Median Extension of Data Analysis Metric Structures -- Text Classification for Mining Massive Aviation Inspection Reports -- A Comparison Between L1 Markov Random Field-Based and Wavelet-Based Estimators -- Elastic and Plastic Splines: Some Experimental Comparisons -- On the Bitplane Compression of Microarray Images -- Overdispersed Regression Models for Air Pollution and Human Health -- Atmospheric Pollution and Mortality in Sรฃo Paulo -- Contributors

1. Mathematics
2. Probabilities
3. Statistics
4. Mathematics
5. Probability Theory and Stochastic Processes
6. Statistical Theory and Methods