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We provide asymptotic results for the distribution of weighted nonlinear functionals of Gaussian field with long-range dependence. We also show that integral functionals and the corresponding additive functionals have same distributions…

Probability · Mathematics 2017-10-06 Tareq Alodat , Andriy Olenko

Functional time series whose sample elements are recorded sequentially over time are frequently encountered with increasing technology. Recent studies have shown that analyzing and forecasting of functional time series can be performed…

Methodology · Statistics 2020-09-22 Ufuk Beyaztas , Han Lin Shang

Probability density function estimation with weighted samples is the main foundation of all adaptive importance sampling algorithms. Classically, a target distribution is approximated either by a non-parametric model or within a parametric…

Machine Learning · Computer Science 2023-10-16 Julien Demange-Chryst , François Bachoc , Jérôme Morio , Timothé Krauth

Functional panels are collections of functional time series, and arise often in the study of high frequency multivariate data. We develop a portmanteau style test to determine if the cross-sections of such a panel are independent and…

Methodology · Statistics 2016-07-12 Piotr Kokoszka , Matthew Reimherr , Nikolas Wölfing

This is the first paper of a series of two devoted to develop a practical method to describe the growth history of bound virialized objects in the gravitational instability scenario without resorting to $N$-body simulations. Here we present…

Astrophysics · Physics 2009-10-28 Alberto Manrique , Eduard Salvador-Sole

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

Methodology · Statistics 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

We consider the error distribution in functional linear models with scalar response and functional covariate. Different asymptotic expansions of the empirical distribution function and the empirical characteristic function based on…

Methodology · Statistics 2025-12-01 Natalie Neumeyer , Leonie Selk

Count-weighted temporal networks often exhibit unequal dispersion in the edge weights, which cannot be fully explained by modelling observational heterogeneity through latent factors in the conditional mean. Therefore, we propose new…

Methodology · Statistics 2026-04-15 Giulia Carallo , Roberto Casarin , Antonio Peruzzi

Diffusion is a key element of a large set of phenomena occurring on natural and social systems modeled in terms of complex weighted networks. Here, we introduce a general formalism that allows to easily write down mean-field equations for…

Statistical Mechanics · Physics 2010-07-14 Andrea Baronchelli , Romualdo Pastor-Satorras

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen

The recently proposed universal relations between the moments of the polydispersity distributions of a phase-separated weakly polydisperse system are analyzed in detail using the numerical results obtained by solving a simple density…

Statistical Mechanics · Physics 2009-10-31 Hong Xu , Marc Baus

We consider a random field $\phi(\mathbf{r})$ in $d$ dimensions which is largely concentrated around small `hotspots', with `weights', $w_i$. These weights may have a very broad distribution, such that their mean does not exist, or else is…

Statistical Mechanics · Physics 2023-11-14 Michael Wilkinson , Boris Veytsman

The equilibrium distribution function determines macroscopic observables in statistical physics. While conventional methods correct equilibrium distributions in weakly nonlinear or near-integrable systems, they fail in strongly nonlinear…

Statistical Mechanics · Physics 2025-07-11 Jialin Zhang , Yong Zhang , Hong Zhao

We develop a model to describe the properties of random assemblies of polydisperse hard spheres. We show that the key features to describe the system are (i) the dependence between the free volume of a sphere and the various coordination…

Disordered Systems and Neural Networks · Physics 2015-05-19 Maximilien Danisch , Yuliang Jin , Hernan A. Makse

We study the asymptotic behavior of stochastic hyperbolic parabolic equations with slow and fast time scales. Both the strong and weak convergence in the averaging principe are established, which can be viewed as a functional law of large…

Probability · Mathematics 2020-11-12 Michael Röckner , Longjie Xie , Li Yang

Jamming criticality defines a universality class that includes systems as diverse as glasses, colloids, foams, amorphous solids, constraint satisfaction problems, neural networks, etc. A particularly interesting feature of this class is…

We consider heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown and to be estimated with nonparametric approaches. We derive convergence rates of posterior distributions for this…

Statistics Theory · Mathematics 2010-10-07 Yuao Hu

This note investigates the relation between squeezing function and its generalizations. Using the relation obtained, we present an alternate method to find expression of generalized squeezing function of unit ball corresponding to the…

Complex Variables · Mathematics 2022-11-30 Naveen Gupta , Sanjay Kumar Pant

This article presents a new class of generalized transmuted lifetime distributions which includes a large number of lifetime distributions as sub-family. Several important mathematical quantities such as density function, distribution…

Methodology · Statistics 2024-05-21 Alok Kumar Pandey , Alam Ali , Ashok Kumar Pathak

The high-pressure compaction of three dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by…

Soft Condensed Matter · Physics 2023-10-19 Joel T. Clemmer , Joseph M. Monti , Jeremy B. Lechman