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Schools with the highest average student performance are often the smallest schools; localities with the highest rates of some cancers are frequently small and the effects observed in clinical trials are likely to be largest for the…

Probability · Mathematics 2016-12-07 Steven N. Evans , Ronald L. Rivest , Philip B. Stark

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 propose eight variants of a practical randomized algorithm where…

Numerical Analysis · Mathematics 2015-01-27 Farbod Roosta-Khorasani , Gábor J. Székely , Uri Ascher

We compared Bayes factors to normalized maximum likelihood for the simple case of selecting between an order-constrained versus a full binomial model. This comparison revealed two qualitative differences in testing order constraints…

Methodology · Statistics 2015-07-01 Daniel W. Heck , Eric-Jan Wagenmakers , Richard D. Morey

Probability distributions defined on the unit interval are widely used in fields ranging from econometrics to reliability studies. Traditional models such as the beta and Kumaraswamy distributions are well-established due to their…

Methodology · Statistics 2026-03-04 Roberto Vila , Helton Saulo , Poliana Matos , Subhankar Dutta

In this paper, we study stochastic non-convex optimization with non-convex random functions. Recent studies on non-convex optimization revolve around establishing second-order convergence, i.e., converging to a nearly second-order optimal…

Optimization and Control · Mathematics 2017-11-02 Mingrui Liu , Tianbao Yang

This paper establishes sharp dimension-free concentration and expectation bounds for the deviation of a sample cross-covariance matrix from its mean. For sub-Gaussian random vectors, we prove a high-probability operator-norm bound governed…

Probability · Mathematics 2026-05-19 Jiaheng Chen , Daniel Sanz-Alonso

Following [OW16], we continue our analysis of: (1) "Quantum tomography", i.e., learning a quantum state, i.e., the quantum generalization of learning a discrete probability distribution; (2) The distribution of Young diagrams output by the…

Quantum Physics · Physics 2016-12-02 Ryan O'Donnell , John Wright

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

In the paper we consider higher-order partial differential equations from the class of linear dispersive equations. We investigate solutions to these equations subject to random initial conditions given by harmonizable…

Probability · Mathematics 2020-03-30 Yuriy Kozachenko , Enzo Orsingher , Lyudmyla Sakhno , Olga Vasylyk

The task of the binary classification problem is to determine which of two distributions has generated a length-$n$ test sequence. The two distributions are unknown; two training sequences of length $N$, one from each distribution, are…

Information Theory · Computer Science 2016-04-18 Dayu Huang , Sean Meyn

In this article, we focus on stochastic orders to compare the magnitudes of two parallel systems from Weibull distributions when one set of scale parameters majorizes the other. The new results obtained here extend some of those proved by…

Statistics Theory · Mathematics 2021-02-19 Nuria Torrado , Subhash C. Kochar

First order stochastic dominance and monotone likelihood ratio are two partial orders on the $n$-probability simplex that play an important role in the establishment of structural results for MDPs and POMDPs. We study the strength of those…

Probability · Mathematics 2020-04-14 Sela Fried

Researchers are often interested in drawing inferences regarding the order between two experimental groups on the basis of multivariate response data. Since standard multivariate methods are designed for two-sided alternatives, they may not…

Statistics Theory · Mathematics 2013-03-11 Ori Davidov , Shyamal Peddada

Non-deterministic measurements are common in real-world scenarios: the performance of a stochastic optimization algorithm or the total reward of a reinforcement learning agent in a chaotic environment are just two examples in which…

Machine Learning · Statistics 2022-08-31 Etor Arza , Josu Ceberio , Ekhiñe Irurozki , Aritz Pérez

For two large matrices ${\mathbf X}$ and ${\mathbf Y}$ with Gaussian i.i.d.\ entries and dimensions $T\times N_X$ and $T\times N_Y$, respectively, we derive the probability distribution of the singular values of $\mathbf{X}^T \mathbf{Y}$ in…

Statistics Theory · Mathematics 2025-08-29 Arabind Swain , Sean Alexander Ridout , Ilya Nemenman

In this article, we revisit the paper by Kundu et al.~(2024), presenting new results and insights for both identical and non-identical independent random variables. We derive sufficient conditions for preserving the hazard rate and reversed…

Applications · Statistics 2025-07-10 Bidhan Modok , Shovan Chowdhury , Amarjit Kundu

For a zero-mean, unit-variance second-order stationary univariate Gaussian process we derive the probability that a record at the time $n$, say $X_n$, takes place and derive its distribution function. We study the joint distribution of the…

Statistics Theory · Mathematics 2018-08-08 Michael Falk , Amir Khorrami , Simone A. Padoan

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…

In this investigation, the distribution of the ratio of two independently distributed xgamma (Sen et al. 2016) random variables X and Y , with different parameters, is proposed and studied. The related distributional properties such as,…

Methodology · Statistics 2024-02-23 Subhradev Sen , Suman K. Ghosh , Hazem Al-Mofleh

Given a sequence of random variables ${\bf X}=X_1,X_2,\ldots$ suppose the aim is to maximize one's return by picking a `favorable' $X_i$. Obviously, the expected payoff crucially depends on the information at hand. An optimally informed…

Statistics Theory · Mathematics 2017-10-02 Uwe Saint-Mont