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The dynamical likelihood method for analysis of high energy collider events is reformulated. The method is to reconstruct the elementary parton state from observed quantities. The basic assumption is that each of final state partons…

High Energy Physics - Experiment · Physics 2007-05-23 Kunitaka Kondo

The fractional Poisson process has recently attracted experts from several fields of study. Its natural generalization of the ordinary Poisson process made the model more appealing for real-world applications. In this paper, we generalized…

Probability · Mathematics 2014-03-06 Dexter O. Cahoy , Federico Polito

The problem of determining the joint probability distributions for correlated random variables with pre-specified marginals is considered. When the joint distribution satisfying all the required conditions is not unique, the "most unbiased"…

Statistical Mechanics · Physics 2015-06-12 Hernán Larralde

We prove an exact fourth moment bound for the normal approximation of random variables belonging to the Wiener chaos of a general Poisson random measure. Such a result -- that has been elusive for several years -- shows that the so-called…

Probability · Mathematics 2021-04-01 Christian Döbler , Giovanni Peccati

In this paper, we give an upper bound for a probabilistic distance between a Gaussian vector and a vector of U-statistics of Poisson point processes by applying Malliavin-Stein inequality on the Poisson space.

Probability · Mathematics 2011-11-10 Nguyen Tuan Minh

The time it takes the fastest searcher out of $N\gg1$ searchers to find a target determines the timescale of many physical, chemical, and biological processes. This time is called an extreme first passage time (FPT) and is typically much…

Probability · Mathematics 2019-12-10 Sean D Lawley

This paper provides a precise error analysis for the maximum likelihood estimate $\hat{a}_{\text{ML}}(u_1^n)$ of the parameter $a$ given samples $u_1^n = (u_1, \ldots, u_n)'$ drawn from a nonstationary Gauss-Markov process $U_i = a U_{i-1}…

Information Theory · Computer Science 2021-03-29 Peida Tian , Victoria Kostina

Real count data time series often show the phenomenon of the underdispersion and overdispersion. In this paper, we develop two extensions of the first-order integer-valued autoregressive process with Poisson innovations, based on binomial…

Methodology · Statistics 2020-07-27 Marcelo Bourguignon , Josemar Rodrigues , Manoel Santos-Neto

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

A new characterization of the exponential distribution is obtained. It is based on an equation involving randomly shifted (translated) order statistics. No specific distribution is assumed for the shift random variables. The proof uses a…

Probability · Mathematics 2017-01-05 Santanu Chakraborty , George P. Yanev

We investigate continuum percolation for Cox point processes, that is, Poisson point processes driven by random intensity measures. First, we derive sufficient conditions for the existence of non-trivial sub- and super-critical percolation…

Probability · Mathematics 2017-11-01 Christian Hirsch , Benedikt Jahnel , Elie Cali

This paper presents some new results on the conditional joint probability distributions of phase-type under the mixture of right-continuous Markov jump processes with absorption on the same finite state space $\mathbb{S}$ moving at…

Probability · Mathematics 2018-07-24 B. A. Surya

Simulating samples from arbitrary probability distributions is a major research program of statistical computing. Recent work has shown promise in an old idea, that sampling from a discrete distribution can be accomplished by perturbing and…

Computation · Statistics 2016-04-13 Chris J. Maddison

We study the stochastic dynamics of a system of interacting species in a stochastic environment by means of a continuous-time Markov chain with transition rates depending on the state of the environment. Models of gene regulation in systems…

Dynamical Systems · Mathematics 2019-12-03 Daniele Cappelletti , Abhishek Pal Majumder , Carsten Wiuf

Max-stable processes have proved to be useful for the statistical modelling of spatial extremes. Several representations of max-stable random fields have been proposed in the literature. One such representation is based on a limit of…

Methodology · Statistics 2012-04-26 Richard A. Davis , Claudia Klüppelberg , Christina Steinkohl

We compute the moment of order n of the Poisson stochastic integral of a random process u over a metric space X as a sum that runs over all partitions of {1,...,n} and involves the addition of points to Poisson configurations. This formula…

Probability · Mathematics 2012-04-24 Nicolas Privault

In a Cox model, the partial likelihood, as the product of a series of conditional probabilities, is used to estimate the regression coefficients. In practice, those conditional probabilities are approximated by risk score ratios based on a…

Methodology · Statistics 2025-02-27 Youngjin Cho , Yili Hong , Pang Du

Count data are omnipresent in many applied fields, often with overdispersion due to an excess of zeroes or extreme values. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we focus here on the…

Statistics Theory · Mathematics 2022-04-25 Samuel Valiquette , Frédéric Mortier , Jean Peyhardi , Gwladys Toulemonde

In many complex systems studied in statistical physics, inter-arrival times between events such as solar flares, trades and neuron voltages follow a heavy-tailed distribution. The set of event times is fractal-like, being dense in some time…

Statistics Theory · Mathematics 2020-09-16 Katharina Hees , Smarak Nayak , Peter Straka

In this paper we propose an estimator of the distribution of events of different kinds in a homogeneous Poisson process. We give an explicit solution for the maximum likelihood estimator of the distribution and derive its strong consistency…

Methodology · Statistics 2026-05-12 Dragi Anevski , Vladimir Pastukhov