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20062016
most citedAssessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variables

12 citations · 21 across the 5 of their papers we have counts for

collaborators

6 papers

math.PR2016★ 5 cited

Schur properties of convolutions of gamma random variables

Farbod Roosta-Khorasani, Gabor J. Szekely

Sufficient conditions for comparing the convolutions of heterogeneous gamma random variables in terms of the usual stochastic order are established. Such comparisons are characteri…

stat.CO2014★ 3 cited

Fast Computing for Distance Covariance

Xiaoming Huo, Gabor J. Szekely

Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covari…

stat.ME2014

On a Nonparametric Notion of Residual and its Applications

Rohit Kumar Patra, Bodhisattva Sen, Gabor Szekely

Let be a continuous random vector in , . In this paper, we define the notion of a nonparametric residual of on $\math…

math.NA2014★ 12 cited

Assessing stochastic algorithms for large scale nonlinear least squares problems using extremal probabilities of linear combinations of gamma random variables

Farbod Roosta-Khorasani, Gábor J. Székely, Uri Ascher

This article considers stochastic algorithms for efficiently solving a class of large scale non-linear least squares (NLS) problems which frequently arise in applications. We propo…

stat.ME2013

Partial Distance Correlation with Methods for Dissimilarities

Gabor J. Szekely, Maria L. Rizzo

Distance covariance and distance correlation are scalar coefficients that characterize independence of random vectors in arbitrary dimension. Properties, extensions, and applicatio…

math.ST2006★ 1 cited

Student's -test for scale mixture errors

Gábor J. Székely

Generalized t-tests are constructed under weaker than normal conditions. In the first part of this paper we assume only the symmetry (around zero) of the error distribution (i). In…