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We consider empirical measures in a triangular array setup with underlying distributions varying as sample size grows. We study asymptotic properties of multiple integrals with respect to normalized empirical measures. Limit theorems…

Probability · Mathematics 2024-08-05 Shuyang Bai , Jiemiao Chen

Worst-case bounds on the expected shortfall risk given only limited information on the distribution of the random variables has been studied extensively in the literature. In this paper, we develop a new worst-case bound on the expected…

Risk Management · Quantitative Finance 2017-02-12 Anulekha Dhara , Bikramjit Das , Karthik Natarajan

We establish a dichotomy for the rate of the decay of the Ces\`aro averages of correlations of sufficiently regular functions for typical interval exchange transformations (IET) which are not rigid rotations (for which weak mixing had been…

Dynamical Systems · Mathematics 2021-05-25 Artur Avila , Giovanni Forni , Pedram Safaee

The derivation of effective macroscopic theories approximating microscopic systems of interacting particles is a major question in non-equilibrium statistical mechanics. In these notes we present an approximation of systems made by many…

Mathematical Physics · Physics 2023-07-18 Chiara Saffirio

Formalising the confrontation of opinions (models) to observations (data) is the task of Inferential Statistics. Information Theory provides us with a basic functional, the relative entropy (or Kullback-Leibler divergence), an asymmetrical…

Information Theory · Computer Science 2015-03-13 François Bavaud

While a mature body of work supports the study of rewriting systems, abstract tools for Probabilistic Rewriting are still limited. In this paper we study the question of uniqueness of the result (unique limit distribution), and develop a…

Logic in Computer Science · Computer Science 2023-06-22 Claudia Faggian

We present a class of inequality constraints on the set of distributions induced by local interventions on variables governed by a causal Bayesian network, in which some of the variables remain unmeasured. We derive bounds on causal effects…

Artificial Intelligence · Computer Science 2012-07-02 Changsung Kang , Jin Tian

This paper develops a framework for fitting functions with domains in the Euclidean space, when data are sparse but a slow variation allows for a useful fit. We measure the variation by Lipschitz Bound (LB). Functions which admit smaller LB…

Methodology · Statistics 2014-07-07 Reza Hosseini , Akimichi Takemura , Kiros Berhane

We provide new limit theory for functionals of a general class of processes lying at the boundary between stationarity and nonstationarity -- what we term weakly nonstationary processes (WNPs). This includes, as leading examples, fractional…

Statistics Theory · Mathematics 2020-08-17 James A. Duffy , Ioannis Kasparis

Finite sample bounds on the estimation error of the mean by the empirical mean, uniform over a class of functions, can often be conveniently obtained in terms of Rademacher or Gaussian averages of the class. If a function of n variables has…

Probability · Mathematics 2015-03-10 Andreas Maurer

We consider polynomial long-range Ising models in one dimension, with ferromagnetic pair interactions decaying with power $2-\alpha$ (for $0 \leq \alpha < 1$), and prepared with randomly chosen boundary conditions. We show that at low…

Mathematical Physics · Physics 2024-05-17 Eric O. Endo , Aernout C. D. van Enter , Arnaud Le Ny

The paper deals with the asymptotic laws of functional of standard random variables. These classes of statistics are closely related to estimators of the extreme value index when the underlying distribution function is in the Weibull domain…

Methodology · Statistics 2016-11-22 Gane Samb Lo , Adja Mbarka Fall , Cheikhna Hamallah Ndiaye , Akym Adekpejou

Empirical processes for stationary, causal sequences are considered. We establish empirical central limit theorems for classes of indicators of left half lines, absolutely continuous functions and piecewise differentiable functions. Sample…

Statistics Theory · Mathematics 2007-06-13 Wei Biao Wu

The advantages of adaptive experiments have led to their rapid adoption in economics, other fields, as well as among practitioners. However, adaptive experiments pose challenges for causal inference. This note suggests a BOLS (batched…

Econometrics · Economics 2025-12-12 Jan Kemper , Davud Rostam-Afschar

Robust risk minimisation has several advantages: it has been studied with regards to improving the generalisation properties of models and robustness to adversarial perturbation. We bound the distributionally robust risk for a model class…

Machine Learning · Statistics 2018-09-06 Zac Cranko , Simon Kornblith , Zhan Shi , Richard Nock

We develop sensitivity analyses for weak nulls in matched observational studies while allowing unit-level treatment effects to vary. The methods may be applied to studies using any optimal without-replacement matching algorithm. In contrast…

Methodology · Statistics 2020-02-18 Colin B. Fogarty

Dynamic logit models are popular tools in economics to measure state dependence. This paper introduces a new method to derive moment restrictions in a large class of such models with strictly exogenous regressors and fixed effects. We…

Econometrics · Economics 2023-12-05 Kevin Dano

In this work we review some recent development in the mathematical modelling of quantitative sociology by means of statistical mechanics. After a short pedagogical introduction to static and dynamic properties of many body systems, we…

Physics and Society · Physics 2009-10-15 Elena Agliari , Adriano Barra , Raffaella Burioni , Pierluigi Contucci

We construct marked Gibbs point processes in $\mathbb{R}^d$ under quite general assumptions. Firstly, we allow for interaction functionals that may be unbounded and whose range is not assumed to be uniformly bounded. Indeed, our typical…

Probability · Mathematics 2022-07-15 Sylvie Roelly , Alexander Zass

Logistic regression involving high-dimensional covariates is a practically important problem. Often the goal is variable selection, i.e., determining which few of the many covariates are associated with the binary response. Unfortunately,…

Computation · Statistics 2025-02-18 Yiqi Tang , Ryan Martin
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