Efficiency-Robust Estimation of Location

Efficiency Constrained Bias Robust Estimation of Location

A Robust Estimation of Location and Scatter

Statisticians face increasingly the task of analyzing large and high dimension multivariate data sets. This is due to the advances in computer technology which have facilitated greatly the collection of large data sets and, on the other hand, to the fact that most statistical experiments are multivariate in nature. One of the primary problems encountered in this task is robust estimation of loc...

Bias Robust Estimation of Scale Where Location Is Unknown

In this paper we consider the problem of robust estimation of the scale of the location residuals when the "true" underlying distribution of the data belongs to a contamination neighborhood of a parametric location-scale family. First we show that a scaled version of the l\tlADAM (median of absolute residuals about the median) is approximately most bias-robust within the class 0 Huber's proposa...

Fast Randomized Algorithms for Robust Estimation of Location

A fundamental procedure appearing within such clustering methods as k-Means, Expectation Maximization, Fuzzy-C-Means and Minimum Message Length is that of computing estimators of location. Most estimators of location exhibiting useful robustness properties require at least quadratic time to compute, far too slow for large data mining applications. In this paper, we propose O(Dn p n)-time random...

Estimation of Source Location Using Curvature Analysis

A quadratic surface can be fitted to potential-field data within 3×3 windows, which allow us to calculate curvature attributes from its coefficients. Phillips (2007) derived an equation depending on the most negative curvature to obtain the depth and structural index of isolated sources from peak values of special functions. They divided the special functions into two categories: Model-specific...