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We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the…

Statistics Theory · Mathematics 2016-02-29 Pier Giovanni Bissiri , Chris Holmes , Stephen Walker

Bayesian inference for models with intractable likelihood functions represents a challenging suite of problems in modern statistics. In this work we analyse the Conway-Maxwell-Poisson (COM-Poisson) distribution, a two parameter…

Computation · Statistics 2020-07-13 Alan Benson , Nial Friel

In this paper, we develop simple, yet efficient, procedures for sampling approximations of the two-Parameter Poisson-Dirichlet Process and the normalized inverse-Gaussian process. We compare the efficiency of the new approximations to the…

Computation · Statistics 2012-09-25 Luai Al Labadi , Mahmoud Zarepour

We present a practical way of introducing convolutional structure into Gaussian processes, making them more suited to high-dimensional inputs like images. The main contribution of our work is the construction of an inter-domain inducing…

Machine Learning · Statistics 2017-09-07 Mark van der Wilk , Carl Edward Rasmussen , James Hensman

Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appropriate. We introduce a {novel and probabilistically coherent…

Statistics Theory · Mathematics 2015-03-17 Edoardo M. Airoldi , Thiago Costa , Federico Bassetti , Fabrizio Leisen , Michele Guindani

We study a linear-fractional Bienaym\'e-Galton-Watson process with a general type space. The corresponding tree contour process is described by an alternating random walk with the downward jumps having a geometric distribution. This leads…

Probability · Mathematics 2016-03-07 Alexey Lindo , Serik Sagitov

Most generalized fractional operators rely on prescribed memory kernels, restricting hereditary behavior to predefined forms and limiting flexibility in modeling diverse memory effects. Motivated by these limitations, this paper develops a…

Dynamical Systems · Mathematics 2026-05-27 Jehad Alzabut

In this paper we propose a generalized distribution function of relaxation times (DFRT) considering the Davidson-Cole model as an elementary process instead of the standard Debye model. The distribution function is retrieved from the…

Chemical Physics · Physics 2024-01-15 Anis Allagui , Ahmed Elwakil

For a stochastic process reset at random times, we discuss to what extent the probabilities of some orderings of observables associated with the intervals of time between resetting events are universal, i.e., independent of the choice of…

Statistical Mechanics · Physics 2023-04-28 Claude Godrèche

The paper deals with disorders detection in the multivariate stochastic process. We consider the multidimensional Poisson process or the multivariate renewal process. This class of processes can be used as a description of the distributed…

Optimization and Control · Mathematics 2021-01-12 Krzysztof J. Szajowski

We show that a Gibbs characterization of normalized generalized Gamma processes, recently obtained in Lijoi, Pr\"unster and Walker (2007), can alternatively be derived by exploiting a characterization of exponentially tilted Poisson-Kingman…

Probability · Mathematics 2010-01-02 Annalisa Cerquetti

Network dynamics with point-process-based interactions are of paramount modeling interest. Unfortunately, most relevant dynamics involve complex graphs of interactions for which an exact computational treatment is impossible. To circumvent…

Probability · Mathematics 2022-11-22 François Baccelli , Michel Davydov , Thibaud Taillefumier

Motivated by the growing interest in today's massive parallel computing capabilities we analyze a queueing network with many servers in parallel to which jobs arrive a according to a Poisson process. Each job, upon arrival, is split into…

Probability · Mathematics 2015-07-20 Mariana Olvera-Cravioto , Octavio Ruiz-Lacedelli

We consider here together the inference questions and the change-point problem in Poisson autoregressions (see Tj{\o}stheim, 2012). The conditional mean (or intensity) of the process is involved as a non-linear function of it past values…

Statistics Theory · Mathematics 2013-05-09 Paul Doukhan , William Kengne

In this paper we consider a system with two carousels operated by one picker. The items to be picked are randomly located on the carousels and the pick times follow a phase-type distribution. The picker alternates between the two carousels,…

Probability · Mathematics 2014-04-23 Maria Vlasiou , Ivo J. B. F. Adan , Jaap Wessels

Commonalities and differences in correlation analysis in terms of phase space, conditioning and uncorrelatedness are discussed. The Poisson process is not generally appropriate as reference distribution for normalisation and cumulants, so…

High Energy Physics - Experiment · Physics 2007-05-23 H. C. Eggers

Poisson restart assumes that a stochastic process is interrupted and starts again at random time moments. A number of studies have demonstrated that this strategy may minimize the expected completion time in some classes of random search…

Statistical Mechanics · Physics 2024-05-15 Sergey Belan

In this tutorial survey we recall the basic properties of the special function of the Mittag-Leffler and Wright type that are known to be relevant in processes dealt with the fractional calculus. We outline the major applications of these…

General Mathematics · Mathematics 2021-08-29 Francesco Mainardi

The Poisson process, especially the nonhomogeneous Poisson process (NHPP), is an essentially important counting process with numerous real-world applications. Up to date, almost all works in the literature have been on the estimation of…

Machine Learning · Computer Science 2024-10-28 Son Nguyen Van , Hoai Nguyen Xuan

The formal term-by-term differentiation with respect to parameters is demonstrated to be legitimate for the Mittag-Leffler type functions. The justification of differentiation formulas is made by using the concept of the uniform…

General Mathematics · Mathematics 2024-11-26 Sergei V. Rogosin , Filippo Giraldi , Francesco Mainardi
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