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We introduce stochastic models for continuous-time evolution of angles and develop their estimation. We focus on studying Langevin diffusions with stationary distributions equal to well-known distributions from directional statistics, since…

Expressions for the summation of a new series involving the Laguerre polynomials are obtained in terms of generalized hypergeometric functions. These results provide alternative, and in some cases simpler, expressions to those recently…

Complex Variables · Mathematics 2013-08-13 Y. S. Kim , A. K. Rathie , R. B. Paris

In this paper, we introduce a new multivariate discrete distribution which called multivariate unification of generalized Apostol type distribution (UGAT). Several prop- erties are studied as, moments, probability generating function and…

Statistics Theory · Mathematics 2015-06-09 Beih S. El-Desouky , Rabab Gomaa

Consider the well-known Langevin diffusion on $\mathbb{R}^d$ $$\mathrm{d} X_t = -\nabla U(X_t)\,\mathrm{d} t + \sqrt{2}\mathrm{d} B_t, $$ and its Euler-Maruyama discretization given by $$X_{k+1}=X_k-\eta \nabla U(X_k)+\sqrt{2\eta…

Probability · Mathematics 2025-12-23 Tian Shen , Zhonggen Su , Xiaolin Wang

We construct relative Gromov--Witten theory with expanded degenerations in the normal crossings setting and establish a degeneration formula for the resulting invariants. Given a simple normal crossings pair $(X,D)$, we show that there…

Algebraic Geometry · Mathematics 2022-05-03 Dhruv Ranganathan

Due to its heavy-tailed and fully parametric form, the multivariate generalized Gaussian distribution (MGGD) has been receiving much attention for modeling extreme events in signal and image processing applications. Considering the…

Applications · Statistics 2017-02-27 F. Pascal , L. Bombrun , J. Y. Tourneret , Y. Berthoumieu

A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be…

Methodology · Statistics 2018-03-01 Rose Baker

An extension of the Gaussian correlation conjecture (GCC) is proved for multivariate gamma distributions (in the sense of Krishnamoorthy and Parthasarathy). The classical GCC for Gaussian probability measures is obtained by the special case…

Probability · Mathematics 2017-04-01 T. Royen

Multivariate categorical data occur in many applications of machine learning. One of the main difficulties with these vectors of categorical variables is sparsity. The number of possible observations grows exponentially with vector length,…

Machine Learning · Statistics 2015-03-10 Yarin Gal , Yutian Chen , Zoubin Ghahramani

We introduce a multivariate hidden Markov model to jointly cluster time-series observations with different support, i.e. circular and linear. Relying on the general projected normal distribution, our approach allows for bimodal and/or…

Applications · Statistics 2015-01-27 Gianluca Mastrantonio , Antonello Maruotti , Giovanna Jona Lasinio

The generalized gamma distribution shows up in many problems related to engineering, hydrology as well as survival analysis. Earlier work has been done that estimated the deviation of the exponential and the Weibull distribution from…

Probability · Mathematics 2022-11-10 Zelong Bi , Irfan Durmić , Steven J. Miller

We consider properties of determinants of some random symmetric matrices issued from multivariate statistics: Wishart/Laguerre ensemble (sample covariance matrices), Uniform Gram ensemble (sample correlation matrices) and Jacobi ensemble…

Probability · Mathematics 2008-01-30 Alain Rouault

New results on uniform convergence in probability for expansions of Gaussian random processes using compactly supported wavelets are given. The main result is valid for general classes of nonstationary processes. An application of the…

Probability · Mathematics 2013-08-08 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

We prove some invariance principles for processes which generalize FARIMA processes, when the innovations are in the domain of attraction of a nonGaussian stable distribution. The limiting processes are extensions of the fractional L\'evy…

Probability · Mathematics 2010-07-06 Ph. Barbe , W. P. McCormick

A unified, fast, and effective approach is developed for numerical calculation of the well-known plasma dispersion function with extensions from Maxwellian distribution to almost arbitrary distribution functions, such as the $\delta$, flat…

Plasma Physics · Physics 2013-11-20 Hua-sheng Xie

Recent rapid advances in single particle tracking and supercomputing techniques resulted in an unprecedented abundance of diffusion data exhibiting complex behaviours, such the presence of power law tails of the msd and memory functions,…

Statistical Mechanics · Physics 2018-10-08 Jakub Ślęzak

The aim of this paper is to introduce the degenerate generalized Laguerre polynomials as the degenerate version of the generalized Laguerre polynomials and to derive some properties related to those polynomials and Lah numbers, including an…

Classical Analysis and ODEs · Mathematics 2021-07-07 Taekyun Kim , Dmitry V. Dolgy , Dae san Kim , Hye Kyung Kim , Seong Ho Park

Building on the one-to-one relationship between generalized FGM copulas and multivariate Bernoulli distributions, we prove that the class of multivariate distributions with generalized FGM copulas is a convex polytope. Therefore, we find…

Mathematical Finance · Quantitative Finance 2024-10-10 Hélène Cossette , Etienne Marceau , Alessandro Mutti , Patrizia Semeraro

In this paper, we study a mixed variational problem subject to perturbations, where the noise term is modelled by means of a bilinear form that has to be understood to be "small" in some sense. Indeed, we consider a family of such problems…

Numerical Analysis · Mathematics 2020-08-26 A. I. Garralda-Guillem , H. Kunze , D. La Torre , M. Ruiz Galan

This paper addresses the Bayesian calibration of dynamic models with parametric and structural uncertainties, in particular where the uncertain parameters are unknown/poorly known spatio-temporally varying subsystem models. Independent…

Computation · Statistics 2012-11-02 Piyush Tagade , Han-Lim Choi
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