34 citations · 49 across the 9 of their papers we have counts for
11 papers
Representative endowments and uniform Gini orderings of multi-attribute welfare
Karl Mosler
For the comparison of inequality and welfare in multiple attributes the use of generalized Gini indices is proposed. Individual endowment vectors are summarized by using attribute…
Choosing among notions of multivariate depth statistics
Karl Mosler, Pavlo Mozharovskyi
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance from the mean, which is based on the mean and the covariance matrix of the data.…
Classification with the pot-pot plot
Oleksii Pokotylo, Karl Mosler
We propose a procedure for supervised classification that is based on potential functions. The potential of a class is defined as a kernel density estimate multiplied by the class'…
Computing the Oja Median in R: The Package OjaNP
Daniel Fischer, Karl Mosler, Jyrki Möttönen +3
The Oja median is one of several extensions of the univariate median to the multivariate case. It has many nice properties, but is computationally demanding. In this paper, we firs…
Fast computation of Tukey trimmed regions and median in dimension
Xiaohui Liu, Karl Mosler, Pavlo Mozharovskyi
Given data in , a Tukey -trimmed region is the set of all points that have at least Tukey depth w.r.t. the data. As they are visual, affine equivariant and r…
Classifying real-world data with the -procedure
Pavlo Mozharovskyi, Karl Mosler, Tatjana Lange
The -classifier, a nonparametric fast and very robust procedure, is described and applied to fifty classification problems regarding a broad spectrum of real-world data. The p…
Fast DD-classification of functional data
Karl Mosler, Pavlo Mozharovskyi
A fast nonparametric procedure for classifying functional data is introduced. It consists of a two-step transformation of the original data plus a classifier operating on a low-dim…
Stochastic linear programming with a distortion risk constraint
Karl Mosler, Pavel Bazovkin
Linear optimization problems are investigated whose parameters are uncertain. We apply coherent distortion risk measures to capture the possible violation of a restriction. Each ri…
General notions of depth for functional data
Karl Mosler, Yulia Polyakova
A data depth measures the centrality of a point with respect to an empirical distribution. Postulates are formulated, which a depth for functional data should satisfy, and a genera…
Fast nonparametric classification based on data depth
Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
A new procedure, called DDa-procedure, is developed to solve the problem of classifying d-dimensional objects into q >= 2 classes. The procedure is completely nonparametric; it use…
Depth statistics
Karl Mosler
In 1975 John Tukey proposed a multivariate median which is the 'deepest' point in a given data cloud in R^d. Later, in measuring the depth of an arbitrary point z with respect to t…