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A stochastic dynamics $({\bf X}(t))_{t\ge0}$ of a classical continuous system is a stochastic process which takes values in the space $\Gamma$ of all locally finite subsets (configurations) in $\Bbb R$ and which has a Gibbs measure $\mu$ as…

Probability · Mathematics 2007-05-23 Yuri Kondratiev , Eugene Lytvynov , Michael Röckner

The two parameter Poisson-Dirichlet distribution $PD(\alpha,\theta)$ is the distribution of an infinite dimensional random discrete probability. It is a generalization of Kingman's Poisson-Dirichlet distribution. The two parameter Dirichlet…

Probability · Mathematics 2009-03-22 Shui Feng , Wei Sun

The present paper provides exact expressions for the probability distributions of linear functionals of the two-parameter Poisson--Dirichlet process $\operatorname {PD}(\alpha,\theta)$. We obtain distributional results yielding exact forms…

Probability · Mathematics 2009-09-29 Lancelot F. James , Antonio Lijoi , Igor Prünster

We prove that there exists a diffusion process whose invariant measure is the three dimensional polymer measure $\nu_\lambda$ for all $\lambda>0$. We follow in part a previous incomplete unpublished work of the first named author with M.…

Probability · Mathematics 2025-07-25 Sergio Albeverio , Seiichiro Kusuoka , Song Liang , Makoto Nakashima

This paper explores large sample properties of the two-parameter $(\alpha,\theta)$ Poisson--Dirichlet Process in two contexts. In a Bayesian context of estimating an unknown probability measure, viewing this process as a natural extension…

Probability · Mathematics 2008-05-21 Lancelot F. James

The two-parameter Poisson-Dirichlet diffusion takes values in the infinite ordered simplex and extends the celebrated infinitely-many-neutral-alleles model, having a two-parameter Poisson-Dirichlet stationary distribution. Here we identify…

Probability · Mathematics 2024-10-16 Robert C. Griffiths , Matteo Ruggiero , Dario Spanò , Youzhou Zhou

We construct a recurrent diffusion process with values in the space of probability measures over an arbitrary closed Riemannian manifold of dimension $d\ge 2$. The process is associated with the Dirichlet form defined by integration of the…

Probability · Mathematics 2022-04-04 L. Dello Schiavo

In this paper, we are concerned with polymer models based on $\alpha$-stable processes, where $\alpha\in (\frac{d}{2},d\wedge 2)$ and $d$ stands for dimension. They are attached with a delta potential at the origin and the associated Gibbs…

Probability · Mathematics 2019-05-02 Liping Li , Xiaodan Li

We introduce and study interval partition diffusions with Poisson--Dirichlet$(\alpha,\theta)$ stationary distribution for parameters $\alpha\in(0,1)$ and $\theta\ge 0$. This extends previous work on the cases $(\alpha,0)$ and…

Probability · Mathematics 2022-07-25 Noah Forman , Douglas Rizzolo , Quan Shi , Matthias Winkel

We analyse a diffusion process whose invariant measure is the fractional polymer or Edwards measure for fractional Brownian motion in dimension $d\in\mathbb{N}$ with Hurst parameter $H\in(0,1)$ fulfilling $dH < 1$. We make use of a…

Probability · Mathematics 2017-03-31 Wolfgang Bock , Torben Fattler

We prove the existence of a diffusion process whose invariant measure is the fractional polymer or Edwards measure for fractional Brownian motion in dimension $d\in\mathbb{N}$ with Hurst parameter $H\in(0,1)$ fulfilling $dH < 1$. The…

Mathematical Physics · Physics 2019-07-09 Wolfgang Bock , Torben Fattler , Ludwig Streit

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N coupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded…

Mathematical Physics · Physics 2013-03-05 J. Bakosi , J. R. Ristorcelli

Directional data require specialized probability models because of the non-Euclidean and periodic nature of their domain. When a directional variable is observed jointly with linear variables, modeling their dependence adds an additional…

Methodology · Statistics 2022-12-22 Tong Zou , Hal S. Stern

For any $N\ge 2$ and $\alpha=(\alpha_1,\cdots, \alpha_{N+1})\in (0,\infty)^{N+1}$, let $\mu^{(N)}_{\alpha}$ be the Dirichlet distribution with parameter $\alpha$ on the set $\Delta^{ (N)}:= \{ x \in [0,1]^N:\ \sum_{1\le i\le N}x_i \le 1…

Probability · Mathematics 2018-04-10 Feng-Yu Wang , Weiwei Zhang

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner's generalized Dirichlet distribution (R.H. Lochner, A Generalized…

Mathematical Physics · Physics 2013-10-02 J. Bakosi , J. R. Ristorcelli

This paper is devoted to the construction and study of an equilibrium Glauber-type dynamics of infinite continuous particle systems. This dynamics is a special case of a spatial birth and death process. On the space $\Gamma$ of all locally…

Probability · Mathematics 2007-05-23 Yu. Kondratiev , E. Lytvynov

Stochastic Differential Equations (SDEs) serve as a powerful modeling tool in various scientific domains, including systems science, engineering, and ecological science. While the specific form of SDEs is typically known for a given…

Methodology · Statistics 2024-02-27 Xin Cai , Jingyu Yang , Zhibao Li , Hongqiao Wang , Miao Huang

Given a compact doubling metric measure space $X$ that supports a $2$-Poincar\'e inequality, we construct a Dirichlet form on $N^{1,2}(X)$ that is comparable to the upper gradient energy form on $N^{1,2}(X)$. Our approach is based on the…

Metric Geometry · Mathematics 2023-10-24 Almaz Butaev , Liangbing Luo , Nageswari Shanmugalingam

We analyze the properties of arguably the simplest bilinear stochastic multiplicative process, proposed as a model of financial returns and of other complex systems combining both nonlinearity and multiplicative noise. By construction, it…

Data Analysis, Statistics and Probability · Physics 2009-11-13 D. Sornette , V. F. Pisarenko

Dirichlet processes and their extensions have reached a great popularity in Bayesian nonparametric statistics. They have also been introduced for spatial and spatio-temporal data, as a tool to analyze and predict surfaces. A popular…

Statistics Theory · Mathematics 2023-03-31 Clara Grazian
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