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This study considers a new multi-term urn process that has a correlation in the same term and temporal correlation. The objective is to clarify the relationship between the urn model and the Hawkes process. Correlation in the same term is…

Statistical Mechanics · Physics 2022-09-14 Masato Hisakado , Kodai Hattori , Shintaro Mori

A beta-negative binomial (BNB) process is proposed, leading to a beta-gamma-Poisson process, which may be viewed as a "multi-scoop" generalization of the beta-Bernoulli process. The BNB process is augmented into a beta-gamma-gamma-Poisson…

Machine Learning · Statistics 2012-02-07 Mingyuan Zhou , Lauren Hannah , David Dunson , Lawrence Carin

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability…

Methodology · Statistics 2013-10-15 Mingyuan Zhou , Lawrence Carin

By developing data augmentation methods unique to the negative binomial (NB) distribution, we unite seemingly disjoint count and mixture models under the NB process framework. We develop fundamental properties of the models and derive…

Machine Learning · Statistics 2013-02-18 Mingyuan Zhou , Lawrence Carin

We discuss various statistical distributions of earthquake numbers. Previously we derived several discrete distributions to describe earthquake numbers for the branching model of earthquake occurrence: these distributions are the Poisson,…

Geophysics · Physics 2010-11-24 Yan Y. Kagan

The negative binomial distribution (NBD) has been theorized to express a scale-invariant property of many-body systems and has been consistently shown to outperform other statistical models in both describing the multiplicity of…

High Energy Physics - Phenomenology · Physics 2023-10-09 S. V. Tezlaf

This paper introduces the class of multidimensional self-exciting processes with dependencies (MSPD), which is a unifying writing for a large class of processes: counting, loss, intensity, and also shifted processes. The framework takes…

Probability · Mathematics 2025-03-27 Caroline Hillairet , Thomas Peyrat , Anthony Réveillac

We develop a Bayesian nonparametric approach to a general family of latent class problems in which individuals can belong simultaneously to multiple classes and where each class can be exhibited multiple times by an individual. We introduce…

Methodology · Statistics 2013-06-11 Tamara Broderick , Lester Mackey , John Paisley , Michael I. Jordan

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour

In this article, a generalized version of Negative binomial-beta exponential distribution with five parameters have been introduced. Some interesting submodels have been derived from it. A comprehensive mathematical treatment of proposed…

Statistics Theory · Mathematics 2019-05-31 Anwar Hassan , Ishfaq Shah Ahmad , Peer Bilal Ahmad

In this paper, we first define the multivariate tempered space-fractional Poisson process (MTSFPP) by time-changing the multivariate Poisson process with an independent tempered {\alpha}-stable subordinator. Its distributional properties,…

Probability · Mathematics 2024-05-24 Ashok Kumar Pathak , Ritik Soni

In this comprehensive and detailed study, vacancy-mediated self-diffusion of A- and B-elements in 'triple-defect' B2-ordered ASB(1-S) binaries is simulated by means of a kinetic Monte Carlo (KMC) algorithm involving atomic jumps to…

Materials Science · Physics 2019-10-16 Jan Betlej , Piotr Sowa , Rafal Kozubski , Graeme E. Murch , Irina V. Belova

Neural network approaches for meta-learning distributions over functions have desirable properties such as increased flexibility and a reduced complexity of inference. Building on the successes of denoising diffusion models for generative…

Machine Learning · Statistics 2023-06-08 Vincent Dutordoir , Alan Saul , Zoubin Ghahramani , Fergus Simpson

We study the continuous time limit of a self-exciting negative binomial process and discuss the critical properties of its intensity distribution. In this limit, the process transforms into a marked Hawkes process. The probability mass…

Probability · Mathematics 2023-05-24 Kotaro Sakuraba , Wataru Kurebayashi , Masato Hisakado , Shintaro Mori

We develop a new class of dynamic multivariate Poisson count models that allow for fast online updating and we refer to these models as multivariate Poisson-scaled beta (MPSB). The MPSB model allows for serial dependence in the counts as…

Methodology · Statistics 2016-09-16 Tevfik Aktekin , Nicholas G. Polson , Refik Soyer

Comparing neuronal bursting models (NBM) with slow-fast autonomous dynamical systems (S-FADS), it appears that the specific features of a (NBM) do not allow a determination of the analytical slow manifold equation with the singular…

Dynamical Systems · Mathematics 2014-08-19 Jean-Marc Ginoux , Bruno Rossetto

We associate learning and adaptation in living systems with the shaping of the velocity vector field in the respective dynamical systems in response to external, generally random, stimuli. With this, a mathematical concept of self-shaping…

Adaptation and Self-Organizing Systems · Physics 2015-10-08 Natalia B. Janson , Christopher J. Marsden

When $S=(S_t)_{t\ge 0}$ is an $\alpha$-stable subordinator, the sequence of ordered jumps of $S$, up till time $1$, omitting the $r$ largest of them, and taken as proportions of their sum $^{(r)}S_t$, defines a 2-parameter distribution on…

Probability · Mathematics 2017-03-30 Yuguang F. Ipsen , Ross A. Maller

In this paper, we introduce a space fractional negative binomial (SFNB) process by subordinating the space fractional Poisson process to a gamma subordinator. Its one-dimensional distributions are derived in terms of generalized Wright…

Probability · Mathematics 2016-04-05 L. Beghin , P. Vellaisamy

The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at each trial. Probabilistic methods are essential to understand the functional role of this variance within…

Neurons and Cognition · Quantitative Biology 2016-11-15 Wahiba Taouali , Giacomo Benvenuti , Pascal Wallisch , Frédéric Chavane , Laurent Perrinet
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