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Beta process is the standard nonparametric Bayesian prior for latent factor model. In this paper, we derive a structured mean-field variational inference algorithm for a beta process non-negative matrix factorization (NMF) model with…

Machine Learning · Statistics 2014-12-03 Dawen Liang , Matthew D. Hoffman

In this paper we consider the fractional parts of a general sequence, for example the sequence $\alpha \sqrt{n}$ or $\alpha n^2$. We give a general method, which allows one to show that long-range correlations (correlations where the…

Dynamical Systems · Mathematics 2020-07-21 Christopher Lutsko

We present a unified framework to study threshold functions for the existence of solutions to linear systems of equations in random sets which includes arithmetic progressions, sum-free sets, $B_{h}[g]$-sets and Hilbert cubes. In…

Combinatorics · Mathematics 2019-02-05 Juanjo Rué , Christoph Spiegel , Ana Zumalacárregui

We introduce two non-homogeneous processes: a fractional non-homogeneous Poisson process of order $k$ and and a fractional non-homogeneous P\'olya-Aeppli process of order $k$. We characterize these processes by deriving their non-local…

Probability · Mathematics 2021-05-04 Tetyana Kadankova , Nikolai Leonenko , Enrico Scalas

Contrary to the classical wisdom, processes with independent values (defined properly) are much more diverse than white noise combined with Poisson point processes, and product systems are much more diverse than Fock spaces. This text is a…

Probability · Mathematics 2007-05-23 Boris Tsirelson

In this paper, we consider a fractional Poisson random field (FPRF) on positive plane. It is defined as a process whose one dimensional distribution is the solution of a system of fractional partial differential equations. A time-changed…

Probability · Mathematics 2024-07-23 K. K. Kataria , P. Vishwakarma

We study the $\beta$ analogue of the nonintersecting Poisson random walks. We derive a stochastic differential equation of the Stieltjes transform of the empirical measure process, which can be viewed as a dynamical version of the…

Probability · Mathematics 2021-03-02 Jiaoyang Huang

Under explicit diophantine conditions on $(\alpha,\beta)\in\RR^2$, we prove that the local two-point correlations of the sequence given by the values $(m-\alpha)^2+\break (n-\beta)^2$, with $(m,n)\in\ZZ^2$, are those of a Poisson process.…

Number Theory · Mathematics 2007-05-23 Jens Marklof

We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(alpha) random variables, normalized by their sum, including beta-size-biasing on total length effects (beta < alpha). Depending on the range of alpha,…

Probability · Mathematics 2013-02-26 Thierry Huillet

Assuming that a stochastic process $X=(X_t)_{t\geq 0}$ is a sum of a compound Poisson process $Y=(Y_t)_{t\geq 0}$ with known intensity $\lambda$ and unknown jump size density $f,$ and an independent Brownian motion $Z=(Z_t)_{t\geq 0},$ we…

Statistics Theory · Mathematics 2007-11-06 Shota Gugushvili

The aim of the present work is to show that the results obtained earlier on the approximation of distributions of sums of independent terms by the accompanying compound Poisson laws may be interpreted as rather sharp quantitative estimates…

Probability · Mathematics 2022-08-04 Friedrich Götze , Andrei Yu. Zaitsev

This chapter is an attempt to present a mathematical theory of compound fractional Poisson processes. The chapter begins with the characterization of a well-known L\'evy process: The compound Poisson process. The semi-Markov extension of…

Probability · Mathematics 2011-03-04 Enrico Scalas

It is shown that for a non-decreasing self-similar stochastic process $T$ with independent increments, the range of $T$ forms a Poisson point process with $\sigma$-finite intensity if and only if the one-dimensional distribution of $T(1)$…

Probability · Mathematics 2022-04-14 Jim Pitman , Zhiyi You

We establish Poisson and compound Poisson approximations for stabilizing statistics of $\beta$-mixing point processes and give explicit rates of convergence. Our findings are based on a general estimate of the total variation distance of a…

Probability · Mathematics 2023-10-24 Nicolas Chenavier , Moritz Otto

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

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of AR(1) process with random-coefficient $a \in [0,1)$ when $N$ and time scale $n$ increase at different rate. Assuming that $a$ has a density, regularly…

Statistics Theory · Mathematics 2013-10-23 Vytaute Pilipauskaite , Donatas Surgailis

We analyze a method to produce pairs of non independent Poisson processes $M(t),N(t)$ from positively correlated, self-decomposable, exponential renewals. In particular the present paper provides the family of copulas pairing the renewals,…

Probability · Mathematics 2017-01-16 Nicola Cufaro Petroni , Piergiacomo Sabino

We present new properties for the Fractional Poisson process and the Fractional Poisson field on the plane. A martingale characterization for Fractional Poisson processes is given. We extend this result to Fractional Poisson fields,…

Probability · Mathematics 2018-01-30 Giacomo Aletti , Nikolai Leonenko , Ely Merzbach

We consider a L\'evy process $Y(t)$ that is not permanently observed, but rather inspected at Poisson($\omega$) moments only, over an exponentially distributed time $T_\beta$ with parameter $\beta$. The focus lies on the analysis of the…

Probability · Mathematics 2021-10-26 Onno Boxma , Michel Mandjes

We study sums of independent random variables that take values $0$, $1/2$, or $1$. We show that the probability mass function of the sum splits into two interleaved parts: one supported on the integers and the other supported on the…

Probability · Mathematics 2026-03-11 Mark Broadie , Ina Petkova