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A n-step Pearson-Gamma random walk in Rd starts at the origin and consists of n independent steps with gamma distributed lengths and uniform orientations. The gamma distribution of each step length has a shape parameter q>0. Constrained…

Data Analysis, Statistics and Probability · Physics 2011-07-27 G. Le Caer

We consider random rooted maps without regard to their genus, with fixed large number of edges, and address the problem of limiting distributions for six different parameters: vertices, leaves, loops, root edges, root isthmus, and root…

Combinatorics · Mathematics 2018-02-21 Olivier Bodini , Julien Courtiel , Sergey Dovgal , Hsien-Kuei Hwang

The edges in networks are not only binary, either present or absent, but also take weighted values in many scenarios (e.g., the number of emails between two users). The covariate-$p_0$ model has been proposed to model binary directed…

Statistics Theory · Mathematics 2021-07-24 MengXu , Qiuping Wang

An asymptotic expansion for inverse moments of positive binomial and Poisson distributions is derived. The expansion coefficients of the asymptotic series are given by the positive central moments of the distribution. Compared to previous…

Statistics Theory · Mathematics 2009-01-16 Marko Znidaric

This paper proposes a novel method to estimate the rate parameter of the Poisson distribution. The proposed method employs the Cramer-von Mises type optimization which has been commonly used in estimating parameters of continuous…

Computation · Statistics 2026-05-22 Jiwoong Kim

We investigate a model of random spatial permutations on two-dimensional tori, and establish that the joint distribution of large cycles is asymptotically given by the Poisson--Dirichlet distribution with parameter one. The asymmetry of the…

Probability · Mathematics 2024-06-18 Alan Hammond , Tyler Helmuth

In this paper, we study the asymptotic behavior of a semi-linear slow-fast stochastic partial differential equation with singular coefficients. Using the Poisson equation in Hilbert space, we first establish the strong convergence in the…

Probability · Mathematics 2021-06-09 Michael Röckner , Longjie Xie , Li Yang

Let $X$, $B$ and $Y$ be three Dirichlet, Bernoulli and beta independent random variables such that $X\sim \mathcal{D}(a_0,...,a_d),$ such that $\Pr(B=(0,...,0,1,0,...,0))=a_i/a$ with $a=\sum_{i=0}^da_i$ and such that $Y\sim \beta(1,a).$ We…

Probability · Mathematics 2012-04-12 Pawel Hitczenko , Gerard Letac

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

We consider distributional limit of the Pearson chi-square statistic when the number of classes m increases with the sample size n in such way that $n/\sqrt{m} \to {\lambda}$. Under mild moment conditions, the limit is Gaussian for…

Probability · Mathematics 2016-09-13 Grzegorz A. Rempała , Jacek Wesołowski

We offer two novel characterizations of the Zeta distribution: first, as tractable continuous mixtures of Negative Binomial distributions (with fixed shape parameter, r > 0), and second, as a tractable continuous mixture of Poisson…

Probability · Mathematics 2021-06-07 Jiansheng Dai , Ziheng Huang , Michael R. Powers , Jiaxin Xu

Finite excursions away from zero of a spectrally positive compound Poisson process with a negative drift can always be decomposed into two parts lying above and below zero, respectively. This paper is concerned with the asymptotic…

Probability · Mathematics 2026-03-24 Zhi-Hao Cui , Hao Wu

We introduce a class of two-parameter discrete dispersion models, obtained by combining convolution with a factorial tilting operation, similar to exponential dispersion models which combine convolution and exponential tilting. The…

Statistics Theory · Mathematics 2014-09-29 Bent Jørgensen , Célestin C. Kokonendji

We completely characterize $\Delta$- and local subexponentialities of positive-half compound Poisson distributions and extend the characterization on two-sided distributions. Moreover, $\Delta$-subexponentiality of infinitely divisible…

Probability · Mathematics 2023-02-21 Muneya Matsui , Toshiro Watanabe

This paper explores various distributional aspects of random variables defined as the ratio of two independent positive random variables where one variable has an $\alpha$-stable law, for $0<\alpha<1$, and the other variable has the law…

Probability · Mathematics 2010-10-22 Lancelot F. James

Fix a base B and let zeta have the standard exponential distribution; the distribution of digits of zeta base B is known to be very close to Benford's Law. If there exists a C such that the distribution of digits of C times the elements of…

Probability · Mathematics 2010-11-16 Steven J. Miller , Mark. J. Nigrini

Large sample size equivalence between the celebrated {\it approximated} Good-Turing estimator of the probability to discover a species already observed a certain number of times (Good, 1953) and the modern Bayesian nonparametric counterpart…

Statistics Theory · Mathematics 2019-01-29 Annalisa Cerquetti

We introduce diffusions on a space of interval partitions of the unit interval that are stationary with the Poisson-Dirichlet laws with parameters $(\alpha,0)$ and $(\alpha,\alpha)$. The construction has two steps. The first is a general…

Probability · Mathematics 2019-10-18 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

A tempered version of the discrete Linnik distribution is introduced in order to obtain integer-valued distribution families connected to stable laws. The proposal constitutes a generalization of the well-known Poisson-Tweedie law, which is…

Statistics Theory · Mathematics 2016-05-10 Lucio Barabesi , Carolina Becatti , Marzia Marcheselli

This paper presents the Poisson-randomized gamma dynamical system (PRGDS), a model for sequentially observed count tensors that encodes a strong inductive bias toward sparsity and burstiness. The PRGDS is based on a new motif in Bayesian…

Machine Learning · Statistics 2019-10-30 Aaron Schein , Scott W. Linderman , Mingyuan Zhou , David M. Blei , Hanna Wallach
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