Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications, Proceedings of a DIMACS Workshop, New Brunswick, New Jersey, USA, May 14-16, 2003

Depth functions in nonparametric multivariate inference by R. Serfling Rank tests for multivariate scale difference based on data depth by R. Y. Liu and K. Singh On scale curves for nonparametric description of dispersion by J. Wang and R. Serfling Data analysis and classification with the zonoid depth by K. Mosler and R. Hoberg On some parametric, nonparametric and semiparametric discrimination rules by A. Hartikainen and H. Oja Regression depth and support vector machine by A. Christmann Spherical data depth and a multivariate median by R. T. Elmore, T. P. Hettmansperger, and F. Xuan Depth-based classification for functional data by S. Lopez-Pintado and J. Romo Impartial trimmed means for functional data by J. A. Cuesta-Albertos and R. Fraiman Geometric measures of data depth by G. Aloupis Computation of half-space depth using simulated annealing by B. Chakraborty and P. Chaudhuri Primaldual algorithms for data depth by D. Bremner, K. Fukuda, and V. Rosta Simplicial depth: An improved definition, analysis, and efficiency for the finite sample case by M. A. Burr, E. Rafalin, and D. L. Souvaine Fast algorithms for frames and point depth by J. H. Dula Statistical data depth and the graphics hardware by S. Krishnan, N. H. Mustafa, and S. Venkatasubramanian.