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It is possible to approach regression analysis with random covariates from a semiparametric perspective where information is combined from multiple multivariate sources. The approach assumes a semiparametric density ratio model where…

Methodology · Statistics 2012-10-02 Anastasia Voulgaraki , Benjamin Kedem , Barry I. Graubard

This article presents a homogeneity test for testing the equality of several high-dimensional covariance matrices for stationary processes with ignoring the assumption of normality. We give the asymptotic distribution of the proposed test.…

Statistics Theory · Mathematics 2020-08-24 Abdullah Qayed , Dong Han

A general theory of inhomogeneous broadening is rarely applied to nonlinear spectroscopy in lieu of either a simple Lorentzian or Gaussian model. In this work, we generalize all the important third-order nonlinear susceptibility expressions…

Optics · Physics 2008-02-26 Robert J. Kruhlak , Mark G. Kuzyk

Most machine learning algorithms, such as classification or regression, treat the individual data point as the object of interest. Here we consider extending machine learning algorithms to operate on groups of data points. We suggest…

Machine Learning · Computer Science 2021-01-15 Danica J. Sutherland , Liang Xiong , Barnabás Póczos , Jeff Schneider

Complex data are often represented as a graph, which in turn can often be viewed as a realisation of a random graph, such as an inhomogeneous random graph model (IRG). For general fast goodness-of-fit tests in high dimensions, kernelised…

Machine Learning · Statistics 2026-04-02 Anum Fatima , Gesine Reinert

Inspired by the modeling of grain growth in polycrystalline materials, we consider a nonlinear Fokker-Plank model, with inhomogeneous diffusion and with variable mobility parameters. We develop large time asymptotic analysis of such…

Analysis of PDEs · Mathematics 2022-06-24 Yekaterina Epshteyn , Chang Liu , Chun Liu , Masashi Mizuno

We tackle the problem of modeling light scattering in homogeneous translucent material and estimating its scattering parameters. A scattering phase function is one of such parameters which affects the distribution of scattered radiation. It…

Computer Vision and Pattern Recognition · Computer Science 2022-09-29 Thanh-Trung Ngo , Hajime Nagahara

A microscopic model is proposed for the interactions between sickle hemoglobin molecules based on information from the protein data bank. A Monte Carlo simulation of a simplified two patch model is carried out, with the goal of…

Soft Condensed Matter · Physics 2009-11-11 Andrey Shiryayev , Xiaofei Li , James D. Gunton

While nonlinear optical spectroscopy is becoming more commonly used to study the excited states of nonlinear-optical systems, a general theory of inhomogeneous broadening is rarely applied in lieu of either a simple Lorentzian or Gaussian…

Optics · Physics 2008-02-26 Robert J. Kruhlak , Mark G. Kuzyk

In previous theoretical research, we inferred that cancer stem cells (CSCs), the cells that presumably drive tumor growth and resistance to conventional cancer treatments, are not uniformly distributed in the bulk of a tumorsphere. To…

Quantitative Methods · Quantitative Biology 2024-03-06 Jerónimo Fotinós , María Paula Marks , Lucas Barberis , Luciano Vellón

Pairs of equivalent Gaussian distributions for centered stationary processes on homogeneous spaces can be characterized in terms of their spectral measures. The purpose of this note is to consider part of the latter characterization from…

Probability · Mathematics 2026-01-27 Michael Hediger

We present the discrete version of heat kernel smoothing on graph data structure. The method is used to smooth data in an irregularly shaped domains in 3D images. New statistical properties are derived. As an application, we show how to…

Methodology · Statistics 2017-10-24 Moo K. Chung , Yanli Wang , Gurong Wu

We present a new class of models for assessing the cell dynamics characterising muscular dystrophies. The proposed approach comprises a system of integro-differential equations for the statistical distributions, over a large patient cohort,…

Analysis of PDEs · Mathematics 2025-11-20 Tommaso Lorenzi , Horacio Tettamanti , Mattia Zanella

The aim of the paper is to construct spatial models for the activation of sweat glands for healthy subjects and subjects suffering from peripheral neuropathy by using videos of sweating recorded from the subjects. The sweat patterns are…

Methodology · Statistics 2021-11-22 Mikko Kuronen , Mari Myllymäki , Adam Loavenbruck , Aila Särkkä

We investigated the effective influence of grain structures on the heat transfer between a fluid and solid domain using mathematical homogenization. The presented model consists of heat equations inside the different domains, coupled…

Analysis of PDEs · Mathematics 2024-07-18 Tom Freudenberg , Michael Eden

We consider an infinite spatial inhomogeneous random graph model with an integrable connection kernel that interpolates nicely between existing spatial random graph models. Key examples are versions of the weight-dependent random connection…

Probability · Mathematics 2023-06-21 Remco van der Hofstad , Pim van der Hoorn , Neeladri Maitra

Modelling epidemics is crucial for understanding the emergence, transmission, impact and control of diseases. Spatial individual-level models (ILMs) that account for population heterogeneity are a useful tool, accounting for factors such as…

Computation · Statistics 2024-05-03 Chinmoy Roy Rahul , Rob Deardon

We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight function is specified, these summary statistics capture…

Methodology · Statistics 2024-03-13 Nicoletta D'Angelo , Giada Adelfio , Jorge Mateu , Ottmar Cronie

Many of the intriguing properties of blood originate from its cellular nature. Bulk effects, such as viscosity, depend on the local shear rates and on the size of the vessels. While empirical descriptions of bulk rheology are available for…

Computational Engineering, Finance, and Science · Computer Science 2023-05-05 Gabor Zavodszky , Christian Spieker , Benjamin Czaja , Britt van Rooij

Score-based diffusion models in infinite-dimensional function spaces provide a mathematically principled framework for modelling function-valued data, offering key advantages such as resolution invariance and the ability to handle irregular…

Machine Learning · Computer Science 2026-05-06 James Rowbottom , Elizabeth L. Baker , Nick Huang , Ben Adcock , Carola-Bibiane Schönlieb , Alexander Denker