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We study distributions of random vectors whose components are second order polynomials in Gaussian random variables. Assuming that the law of such a vector is not absolutely continuous with respect to Lebesgue measure, we derive some…

Probability · Mathematics 2013-05-28 Vladimir I. Bogachev , Egor D. Kosov , Ivan Nourdin , Guillaume Poly

This is a survey paper concerning some theorems on stochastic convex ordering and their applications to functional inequalities for convex functions. We present the recent results on those subjects

Classical Analysis and ODEs · Mathematics 2017-02-01 Teresa Rajba

The concept of "stochastic precedence" between two real-valued random variables has often emerged in different applied frameworks. In this paper we consider a slightly more general, and completely natural, concept of stochastic precedence…

Probability · Mathematics 2015-06-17 Emilio De Santis , Fabio Fantozzi , Fabio Spizzichino

There are two useful ways to extend nonlinear partial differential inequalities of second order: one uses viscosity theory and the other uses the theory of distributions. This paper considers the convex situation where both extensions can…

Analysis of PDEs · Mathematics 2017-12-12 F. Reese Harvey , H. Blaine Lawson

The stochastic comparisons of parallel and series system are worthy of study. In this paper, we present some stochastic comparisons of parallel and series systems having independent components from Gumble distribution with two parameters…

Statistics Theory · Mathematics 2019-05-03 Surojit Biswas , Nitin Gupta

The usual stochastic order and the likelihood ratio order between probability distributions on the real line are reviewed in full generality. In addition, for the distribution of a random pair $(X,Y)$, it is shown that the conditional…

Statistics Theory · Mathematics 2023-03-08 Lutz Duembgen , Alexandre Moesching

We give necessary and sufficient conditions for two sub-vectors of a random vector with a multivariate extreme value distribution, corresponding to the limit distribution of the maximum of a multidimensional stationary sequence with…

Probability · Mathematics 2010-06-09 Clara Viseu , Luísa Pereira , Ana Paula Martins , Helena Ferreira

Stochastic ordering among distributions has been considered in a variety of scenarios. Economic studies often involve research about the ordering of investment strategies or social welfare. However, as noted in the literature, stochastic…

We consider component-wise equivariant estimation of order restricted location/scale parameters of a general bivariate distribution under quite general conditions on underlying distributions and the loss function. This paper unifies various…

Statistics Theory · Mathematics 2022-07-05 Naresh Garg , Neeraj Misra

Strassen's classical martingale coupling theorem states that two real-valued random variables are ordered in the convex (resp.\ increasing convex) stochastic order if and only if they admit a martingale (resp.\ submartingale) coupling. By…

Probability · Mathematics 2017-05-11 Lasse Leskelä , Matti Vihola

Partial orders are used extensively for modeling and analyzing concurrent computations. In this paper, we define two properties of partially ordered sets: width-extensibility and interleaving-consistency, and show that a partial order can…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-07 Himanshu Chauhan , Vijay K. Garg

We study a class of second order variational inequalities with bilateral constraints. Under certain conditions we show the existence of a unique viscosity solution of these variational inequalities and give a stochastic representation to…

Analysis of PDEs · Mathematics 2007-05-23 Mrinal K Ghosh , K S Mallikarjuna Rao

We introduce a comprehensive method for establishing stochastic orders among order statistics in the i.i.d. case. This approach relies on the assumption that the underlying distribution is linked to a reference distribution through a…

Methodology · Statistics 2024-11-22 Tommaso Lando Idir Arab , Paulo Eduardo Oliveira

Convex combinations of i.i.d. random variables without a finite mean can behave in a strikingly different way from the finite-mean case: as the weight vector becomes more balanced, the resulting combination may become stochastically larger,…

Methodology · Statistics 2026-03-10 Tommaso Lando , Paulo Eduardo Oliveira

In this paper, we study stochastic ordering results between two finite mixtures with single and multiple outliers, assuming subpopulations follow general exponentiated location-scale distributions. For single-outlier mixtures, several…

Statistics Theory · Mathematics 2025-11-04 Raju Bhakta , Kaushik Gupta , Ghobad Saadat Kia , Suchandan Kayal

For two causal structures with the same set of visible variables, one is said to observationally dominate the other if the set of distributions over the visible variables realizable by the first contains the set of distributions over the…

Machine Learning · Statistics 2025-02-24 Marina Maciel Ansanelli , Elie Wolfe , Robert W. Spekkens

We construct a procedure to test the stochastic order of two samples of interval-valued data. We propose a test statistic which belongs to U-statistic and derive its asymptotic distribution under the null hypothesis. We compare the…

Methodology · Statistics 2019-12-05 Hyejeong Choi , Johan Lim , Minjung Kwak , Seongoh Park

In this paper, we are interested in comparing solutions to stochastic Volterra equations for the convex order on the space of continuous $\R^d$-valued paths and for the monotonic convex order when $d=1$. Even if in general these solutions…

Probability · Mathematics 2022-11-21 Benjamin Jourdain , Gilles Pagès

In this paper, we propose second-order sufficient optimality conditions for a very general nonconvex constrained optimization problem, which covers many prominent mathematical programs.Unlike the existing results in the literature, our…

Optimization and Control · Mathematics 2022-11-24 Matus Benko , Helmut Gfrerer , Jane Ye , Jin Zhang , Jinchuan Zhou

In this note, we derive concentration inequalities for random vectors with subGaussian norm (a generalization of both subGaussian random vectors and norm bounded random vectors), which are tight up to logarithmic factors.

Probability · Mathematics 2019-02-12 Chi Jin , Praneeth Netrapalli , Rong Ge , Sham M. Kakade , Michael I. Jordan