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In this paper, we present a new multiscale method which is capable of coupling atomistic and continuum domains for high frequency wave propagation analysis. The problem of non-physical wave reflection, which occurs due to the change in…

Computational Physics · Physics 2014-08-08 Amit K. Patra , S. Gopalakrishnan , Ranjan Ganguli

Polydisperse linear polymer melts can be microscopically described by the tube model and fractal reptation dynamics, while on the macroscopic side the generalized Maxwell model is capable of correctly displaying most of the rheological…

Fluid Dynamics · Physics 2018-02-20 Christian Lang

Meta-analyses are regarded as the highest level in the hierarchy of evidence, yet standard models traditionally concentrated on estimating the mean effect size, often under restrictive assumptions about the underlying distribution, such as…

Other Statistics · Statistics 2026-04-02 Yefeng Yang , Shinichi Nakagawa

We introduce a directed, weighted random graph model, where the edge-weights are independent and beta-distributed with parameters depending on their endpoints. We will show that the row- and column-sums of the transformed edge-weight matrix…

Statistics Theory · Mathematics 2017-08-09 Marianna Bolla , Ahmed Elbanna , Jozsef Mala

Here, we introduce a new class of Lindley generated distributions which results in more flexible model with increasing failure rate (IFR), decreasing failure rate(DFR) and up-side down hazard functions for different choices of parametric…

Statistics Theory · Mathematics 2016-01-07 Deepesh Bhati , Mohd. Aamir Malik , K. K. Jose

We describe a complete theory for walk-based centrality indices in complex networks defined in terms of Mittag-Leffler functions. This overarching theory includes as special cases well-known centrality measures like subgraph centrality and…

Numerical Analysis · Mathematics 2021-12-10 Francesca Arrigo , Fabio Durastante

We introduce the linear operators of fractional integration and fractional differentiation in the framework of the Riemann-Liouville fractional calculus. Particular attention is devoted to the technique of Laplace transforms for treating…

Mathematical Physics · Physics 2008-05-27 Rudolf Gorenflo , Francesco Mainardi

Latent Gaussian models (LGMs) are a popular class of Bayesian hierarchical models that include Gaussian processes, as well as certain spatial models and mixed-effect models. Efficient Bayesian inference of LGMs often requires marginalizing…

Machine Learning · Statistics 2026-05-21 Jinlin Lai , Charles C. Margossian , Daniel R. Sheldon

Various computational challenges arise when applying Bayesian inference approaches to complex hierarchical models. Sampling-based inference methods, such as Markov Chain Monte Carlo strategies, are renowned for providing accurate results…

Methodology · Statistics 2022-03-29 Cristian Chiuchiolo , Janet van Niekerk , Håvard Rue

This article is devoted to derivation of the Laplace transforms of the derivatives with respect to parameters of certain special functions, namely, the Mittag-Leffler type, Wright and Le Roy type functions. These formulas show…

General Mathematics · Mathematics 2025-07-08 Sergei Rogosin , Filippo Giraldi , Francesco Mainardi

A new three-parameter cumulative distribution function defined on $(\alpha,\infty)$, for some $\alpha\geq0$, with asymmetric probability density function and showing exponential decays at its both tails, is introduced. The new distribution…

Statistics Theory · Mathematics 2017-03-28 Meitner Cadena

We establish a new natural extension of Mittag-Leffler function with three variables which is so called "trivariate Mittag-Leffler function". The trivariate Mittag-Leffler function can be expressed via complex integral representation by…

Classical Analysis and ODEs · Mathematics 2020-11-10 Ismail T. Huseynov , Arzu Ahmadovay , Gbenga O. Ojo , Nazim I. Mahmudov

Irregular multivariate time series impose a trade-off for long-horizon forecasting: discrete methods can distort temporal structure via re-gridding, while continuous-time models often require sequential solvers prone to drift. To bridge…

Machine Learning · Computer Science 2026-05-20 Zinuo You , Jin Zheng , John Cartlidge

This work addresses the Galerkin isogeometric discretization of the one-dimensional Laplace eigenvalue problem subject to homogeneous Dirichlet boundary conditions on a bounded interval. We employ GLT theory to analyze the behavior of the…

Numerical Analysis · Mathematics 2025-10-15 Lamsahel Noureddine , Abdeladim El Akri , Ahmed Ratnani

Multi-label classification is prevalent in real-world settings, but the behavior of Large Language Models (LLMs) in this setting is understudied. We investigate how autoregressive LLMs perform multi-label classification, focusing on…

Computation and Language · Computer Science 2025-11-12 Marcus Ma , Georgios Chochlakis , Niyantha Maruthu Pandiyan , Jesse Thomason , Shrikanth Narayanan

Markov processes serve as a universal model for many real-world random processes. This paper presents a data-driven approach for learning these models through the spectral decomposition of the infinitesimal generator (IG) of the Markov…

In this paper considering the transformation $X=\frac{Y}{1+Y}$, where $Y \sim\text{Lindley}(\theta)$, we propose the unit-Lindley distribution and investigate some of its mathematical properties. A important fact associated with this new…

Methodology · Statistics 2018-01-09 J. Mazucheli , A. F. B. Menezes , S. Chakraborty

The main object of this paper is to present a new generalized beta function which defined by three parametres Mittag-Leffler function. We also introduce new generalizations of hypergeometric and confluent hypergeometric functions with the…

Classical Analysis and ODEs · Mathematics 2018-03-09 Muhammed Ay

We consider here the recently proposed closed form formula in terms of the Meijer G-functions for the probability density functions $g_\alpha(x)$ of one-sided L\'evy stable distributions with rational index $\alpha=l/k$, with $0<\alpha<1$.…

Statistical Mechanics · Physics 2011-08-08 Alberto Saa , Roberto Venegeroles

Linear regression models are useful statistical tools to analyze data sets in several different fields. There are several methods to estimate the parameters of a linear regression model. These methods usually perform under normally…

Methodology · Statistics 2020-08-10 Şenay Özdemir , Yeşim Güney , Yetkin Tuaç , Olcay Arslan