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We provide sharp estimates for the distribution function of a martingale transform of the indicator function of an event. They are formulated in terms of Burkholder functions, which are reduced to the already known Bellman functions for…

Classical Analysis and ODEs · Mathematics 2023-10-05 Dmitriy Stolyarov , Vasily Vasyunin , Pavel Zatitskii

In this paper we propose a method to construct probability measures on the space of convex bodies with a given pushforward distribution. Concretely we show that there is a measure on the metric space of centrally symmetric convex bodies,…

Probability · Mathematics 2012-04-27 Á. G. Horváth

A new thresholding method, based on L-statistics and called order thresholding, is proposed as a technique for improving the power when testing against high-dimensional alternatives. The new method allows great flexibility in the choice of…

Statistics Theory · Mathematics 2010-10-21 Min Hee Kim , Michael G. Akritas

It is shown that the convex order between the distributions of linear functionals does not imply the convex order between the probability distributions over $\mathbb R^d$ if $d\ge2$. This stands in contrast with the well-known fact that any…

Probability · Mathematics 2025-10-09 Iosif Pinelis

In this paper we provide a novel family of stochastic orders that generalizes second order stochastic dominance, which we call the $\alpha,[a,b]$-concave stochastic orders. These stochastic orders are generated by a novel set of "very"…

Probability · Mathematics 2021-04-28 Bar Light , Andres Perlroth

This paper provides conditions on the observation probability distribution in Bayesian localization and optimal filtering so that the conditional mean estimate satisfies convex stochastic dominance. Convex dominance allows us to compare the…

Systems and Control · Computer Science 2019-10-29 Vikram Krishnamurthy

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We…

Statistics Theory · Mathematics 2011-08-03 A. Murillo-Salas , F. J. Rubio

Learning high-dimensional distributions is often done with explicit likelihood modeling or implicit modeling via minimizing integral probability metrics (IPMs). In this paper, we expand this learning paradigm to stochastic orders, namely,…

Machine Learning · Statistics 2022-11-11 Carles Domingo-Enrich , Yair Schiff , Youssef Mroueh

For highly skewed or fat-tailed distributions, mean or median-based methods often fail to capture the central tendencies in the data. Despite being a viable alternative, estimating the conditional mode given certain covariates (or mode…

Econometrics · Economics 2024-12-10 Eduardo Schirmer Finn , Eduardo Horta

In this paper, we consider robust control using randomized algorithms. We extend the existing order statistics distribution theory to the general case in which the distribution of population is not assumed to be continuous and the order…

Optimization and Control · Mathematics 2008-05-13 Xinjia Chen , Kemin Zhou

In recent years, stochastic dominance for independent and identically distributed (iid) infinite-mean random variables has received considerable attention. The literature has identified several classes of distributions of nonnegative random…

Probability · Mathematics 2026-04-28 Keyi Zeng , Zhenfeng Zou , Yuting Su , Taizhong Hu

Asymmetric vector norms are generalizations of asymmetric norms, where the subadditivity inequality is understood in ordered vector space sense. This relation imposes strong conditions on the ordering itself. This note studies on these…

Functional Analysis · Mathematics 2020-05-22 A. B. Németh , S. Z. Németh

We study online convex optimization in the random order model, recently proposed by \citet{garber2020online}, where the loss functions may be chosen by an adversary, but are then presented to the online algorithm in a uniformly random…

Machine Learning · Computer Science 2021-06-30 Uri Sherman , Tomer Koren , Yishay Mansour

We consider an independent and identically distributed (i.i.d.) random dynamical system of simple linear transformations on the unit interval $T_{\beta}(x)=\beta x$ (mod $1$), $x\in[0,1]$, $\beta>0$, which are the so-called…

Dynamical Systems · Mathematics 2024-04-26 Shintaro Suzuki

A new class of distributional transformations is introduced, characterized by equations relating function weighted expectations of test functions on a given distribution to expectations of the transformed distribution on the test function's…

Probability · Mathematics 2007-05-23 Larry Goldstein , Gesine Reinert

The mid-p-value is a proposed improvement on the ordinary p-value for the case where the test statistic is partially or completely discrete. In this case, the ordinary p-value is conservative, meaning that its null distribution is larger…

Statistics Theory · Mathematics 2017-06-02 Patrick Rubin-Delanchy , Nicholas A. Heard , Daniel John Lawson

A refinement of the multinomial distribution is presented where the number of inversions in the sequence of outcomes is tallied. This refinement of the multinomial distribution is its joint distribution with the number of inversions in the…

Probability · Mathematics 2025-08-19 Andrew V. Sills

We consider a simple dice game, which leads to an intriguing study of multinomial walks, with surprising and seemingly paradoxical properties. The winning and losing probabilities of a general version of the game are investigated via…

Probability · Mathematics 2026-05-21 Gunther Leobacher , Alexander Steinicke

We study conformal quantum mechanics by first considering the perturbative $S$-matrix in various dimensions. The model has two couplings and we study perturbatively the degree of ultraviolet divergences arising in the interplay between the…

Quantum Physics · Physics 2026-04-20 Jacob Hafjall , Thomas A. Ryttov

In this paper, we discuss the ambiguous chance constrained based portfolio optimization problems, in which the perturbations associated with the input parameters are stochastic in nature, but their distributions are not known precisely. We…

Optimization and Control · Mathematics 2023-11-09 Pulak Swain , Akshay Kumar Ojha
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