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The invariant is one of central topics in science, technology and engineering. The differential invariant is essential in understanding or describing some important phenomena or procedures in mathematics, physics, chemistry, biology or…

Computer Vision and Pattern Recognition · Computer Science 2017-05-26 Erbo Li , Hua Li

Attributes which are infrequently expressed in a population can require weeks or months of counting to reach statistical significance. But replacement in a stable population increases long-term counts to a degree determined by the…

Computational Geometry · Computer Science 2018-08-21 Aubrey G. Jaffer , Martin S. Jaffer

We reconsider the Moran model in continuous time with population size $N$, two allelic types, and selection. We introduce a new particle representation, which we call the labelled Moran model, and which has the same distribution of type…

Populations and Evolution · Quantitative Biology 2013-12-09 Sandra Kluth , Ellen Baake

Advances in neural variational inference have facilitated the learning of powerful directed graphical models with continuous latent variables, such as variational autoencoders. The hope is that such models will learn to represent rich,…

Computation and Language · Computer Science 2017-09-26 Iulian V. Serban , Alexander G. Ororbia , Joelle Pineau , Aaron Courville

Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. In this context, the conventional factor graphs are referred…

Artificial Intelligence · Computer Science 2012-07-19 Yongyi Mao , Frank Kschischang , Brendan J. Frey

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a data set of observations of this vector. The probability distribution…

Probability · Mathematics 2016-08-24 Christian Soize , Roger Ghanem

Dynamic factor models are often estimated by point-estimation methods, disregarding parameter uncertainty. We propose a method accounting for parameter uncertainty by means of posterior approximation, using variational inference. Our…

Methodology · Statistics 2022-10-14 Erik Spånberg

Fractional generalizations of the Poisson process and branching Furry process are considered. The link between characteristics of the processes, fractional differential equations and Levy stable densities are discussed and used for…

Statistical Mechanics · Physics 2010-02-15 Vladimir V. Uchaikin , Dexter O. Cahoy , Renat T. Sibatov

In mathematical finance and other applications of stochastic processes, it is frequently the case that the characteristic function may be known but explicit forms for density functions are not available. The simulation of any distribution…

Computational Finance · Quantitative Finance 2009-03-10 William T. Shaw , Jonathan McCabe

Fractional derivatives are nonlocal differential operators of real order that often appear in models of anomalous diffusion and a variety of nonlocal phenomena. Recently, a version of the Schr\"odinger Equation containing a fractional…

Statistical Mechanics · Physics 2017-09-27 Mamikon Gulian , Haobo Yang , Brenda M. Rubenstein

We consider random matrices that have invariance properties under the action of unitary groups (either a left-right invariance, or a conjugacy invariance), and we give formulas for moments in terms of functions of eigenvalues. Our main tool…

Statistics Theory · Mathematics 2016-09-06 Benoit Collins , Sho Matsumoto , Nadia Saad

Physical and mathematical applications of fractional Poisson probability distribution have been presented. As a physical application, a new family of quantum coherent states has been introduced and studied. As mathematical applications, we…

Mathematical Physics · Physics 2015-05-13 Nick Laskin

The question of the volatility roughness is interpreted in the framework of a data-reconstructed fractional volatility model, where volatility is driven by fractional noise. Some examples are worked out and also, using Malliavin calculus…

General Finance · Quantitative Finance 2024-11-15 R. Vilela Mendes

Functional data analysis involves data described by regular functions rather than by a finite number of real valued variables. While some robust data analysis methods can be applied directly to the very high dimensional vectors obtained…

Machine Learning · Statistics 2012-01-06 Fabrice Rossi , Yves Lechevallier

The problem of inferring the distribution of a random vector given that its norm is large requires modeling a homogeneous limiting density. We suggest an approach based on graphical models which is suitable for high-dimensional vectors. We…

Probability · Mathematics 2022-12-20 Adrien Hitz , Robin Evans

Multivariate functional data present theoretical and practical complications which are not found in univariate functional data. One of these is a situation where the component functions of multivariate functional data are positive and are…

Methodology · Statistics 2023-03-09 Cody Carroll , Hans-Georg Müller

The present paper proposes a robust evaluation of any radial density at small distances using negative-order radial moments evaluated in momentum space. This evaluation provides a valuable insight into the behavior of a given radial density…

Nuclear Theory · Physics 2024-10-18 M. Atoui , M. Hoballah , M. Lassaut , J. Van de Wiele

This article introduces a novel method for detecting distinctive structural changes in economic data, particularly within frequency distribution tables. The approach identifies significant shifts in the distribution of a variable over time…

Applications · Statistics 2025-09-04 Joanna Dębicka , Edyta Mazurek

We show that the kinetic approach to statistical mechanics permits an elegant and efficient treatment of fractional exclusion statistics. By using the exclusion-inclusion principle recently proposed [Phys. Rev. E49, 5103 (1994)] as a…

High Energy Physics - Theory · Physics 2011-08-17 G. Kaniadakis , A. Lavagno , P. Quarati

This paper is devoted to the study of a fractional version of non-linear $\mathpzc{M}^\nu(t)$, $t>0$, linear $M^\nu (t)$, $t>0$ and sublinear $\mathfrak{M}^\nu (t)$, $t>0$ death processes. Fractionality is introduced by replacing the usual…

Probability · Mathematics 2013-04-02 Enzo Orsingher , Federico Polito , Ludmila Sakhno