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Multi-state survival analysis considers several potential events of interest along a disease pathway. Such analyses are crucial to model complex patient trajectories and are increasingly being used in epidemiological and health economic…

Methodology · Statistics 2021-04-30 Jonathan Broomfield , Caroline E. Weibull , Michael J. Crowther

We introduce a new dependence order, termed the conditional convex order, whose minimal and maximal elements characterize independence and perfect dependence. Moreover, it characterizes conditional independence, satisfies information…

Statistics Theory · Mathematics 2026-01-22 Jonathan Ansari , Sebastian Fuchs

Stochastic dominance is an important concept in probability theory, econometrics and social choice theory for robustly modeling agents' preferences between random outcomes. While many works have been dedicated to the univariate case, little…

Machine Learning · Statistics 2024-06-11 Gabriel Rioux , Apoorva Nitsure , Mattia Rigotti , Kristjan Greenewald , Youssef Mroueh

Testing for pairwise independence for the case where the number of variables may be of the same size or even larger than the sample size has received increasing attention in the recent years. We contribute to this branch of the literature…

Statistics Theory · Mathematics 2024-09-18 Axel Bücher , Cambyse Pakzad

A first systematic study of the effects of the choice of the input scale in global determinations of parton distributions and QCD parameters is presented. It is shown that, although in principle the results should not depend on these…

High Energy Physics - Phenomenology · Physics 2014-05-23 Pedro Jimenez-Delgado

Bell inequalities may only be derived, if hidden variables do not depend on the experimental settings. The stochastic independence of hidden and setting variables is called: freedom of choice, free will, measurement independence or no…

Quantum Physics · Physics 2022-04-01 Marian Kupczynski

Order statistics theory is applied in this paper to probabilistic robust control theory to compute the minimum sample size needed to come up with a reliable estimate of an uncertain quantity under continuity assumption of the related…

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

This paper contains a study of multivariate second order stochastic mappings indexed by an abstract set $\Lambda$ in close connection to their operator covariance functions. The characterizations of the normal Hilbert module or of Hilbert…

Functional Analysis · Mathematics 2015-01-27 Pastorel Gaspar , Lorena Popa

In this paper, we have studied the stochastic comparisons of the highest and lowest order statistics of exponentiated Gumble type-II distribution with three parameters. We have compared both the statistics by using three different…

Statistics Theory · Mathematics 2019-04-19 Surojit Biswas , Nitin Gupta

We formulate the statistics of the discrete multicomponent fragmentation event using a methodology borrowed from statistical mechanics. We generate the ensemble of all feasible distributions that can be formed when a single integer…

Statistical Mechanics · Physics 2020-07-03 Themis Matsoukas

In this paper, we investigate a class of multiscale McKean-Vlasov stochastic systems, where the entire system depends on the distributions of both fast and slow components. First of all, by applying the Poisson equation method, we prove…

Probability · Mathematics 2025-09-30 Jie Xiang , Huijie Qiao

Identifying dependency in multivariate data is a common inference task that arises in numerous applications. However, existing nonparametric independence tests typically require computation that scales at least quadratically with the sample…

Methodology · Statistics 2021-07-08 Shai Gorsky , Li Ma

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Despite a plethora of methods have been…

Physics and Society · Physics 2023-03-01 Andrea Santoro , Federico Battiston , Giovanni Petri , Enrico Amico

The concepts of probability, statistics and stochastic theory are being successfully used in structural engineering. Markov Chain modelling is a simple stochastic process model that has found its application in both describing stochastic…

Applications · Statistics 2007-08-14 K. Balaji Rao

The Stochastic Block Model (Holland et al., 1983) is a mixture model for heterogeneous network data. Unlike the usual statistical framework, new nodes give additional information about the previous ones in this model. Thereby the…

Statistics Theory · Mathematics 2011-11-01 Antoine Channarond , Jean-Jacques Daudin , Stéphane Robin

We study decision dependent distributionally robust optimization models, where the ambiguity sets of probability distributions can depend on the decision variables. These models arise in situations with endogenous uncertainty. The developed…

Optimization and Control · Mathematics 2018-06-26 Fengqiao Luo , Sanjay Mehrotra

This paper develops a Bayesian control chart for the percentiles of the Weibull distribution, when both its in-control and out-of-control parameters are unknown. The Bayesian approach enhances parameter estimates for small sample sizes that…

Methodology · Statistics 2013-08-06 Pasquale Erto , Giuliana Pallotta , Christina M. Mastrangelo

As a motivating problem, we aim to study some special aspects of the marginal distributions of the order statistics for exchangeable and (more generally) for minimally stable non-negative random variables $T_{1},...,T_{r}$. In any case, we…

Probability · Mathematics 2021-06-16 Rachele Foschi , Giovanna Nappo , Fabio L. Spizzichino

We consider two models of two-units repairable systems: cold standby system and warm standby system. We suppose that the lifetimes and repair times of the units are all independent exponentially distributed random variables. Using…

Probability · Mathematics 2020-07-08 J. M. Corujo , J. E. Valdés , J. C Laria

We discuss Bayesian nonparametric procedures for the regression analysis of compositional responses, that is, data supported on a multivariate simplex. The procedures are based on a modified class of multivariate Bernstein polynomials and…

Methodology · Statistics 2021-08-31 Claudia Wehrhahn , Andrés F. Barrientos , Alejandro Jara