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The computational method of parametric probability analysis is introduced. It is demonstrated how to embed logical formulas from the propositional calculus into parametric probability networks, thereby enabling sound reasoning about the…

Logic · Mathematics 2012-05-24 Joseph W. Norman

Based on the probability distribution observed in complex systems and an assumption that the probability distributions of complex systems satisfy a new generalized multiplication, it is proved that the statistical theory of complex systems…

Statistical Mechanics · Physics 2015-06-25 Jincan Chen , Tie Liu , Zhifu Huang , Guozhen Su

The solution of Poisson's equation plays a key role in constructing the martingale through which sums of Markov correlated random variables can be analyzed. In this paper, we study two different representations for the solution in countable…

Probability · Mathematics 2022-02-22 Peter W. Glynn , Alex Infanger

We describe a procedure to introduce general dependence structures on a set of Dirichlet processes. Dependence can be in one direction to define a time series or in two directions to define spatial dependencies. More directions can also be…

Methodology · Statistics 2021-10-18 Luis E. Nieto-Barajas

The phenomenology of turbulent relative dispersion is revisited. A heuristic scenario is proposed, in which pairs of tracers undergo a succession of independent ballistic separations during time intervals whose lengths fluctuate. This…

Fluid Dynamics · Physics 2015-06-19 Simon Thalabard , Giorgio Krstulovic , Jeremie Bec

Reciprocal space methods for solving Poisson's equation for finite charge distributions are investigated. Improvements to previous proposals are presented, and their performance is compared in the context of a real-space density functional…

Computational Physics · Physics 2007-05-23 Alberto Castro , Angel Rubio , M. J. Stott

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

If a given aggregate process $S$ is a compound mixed renewal process under a probability measure $P$, we provide a characterization of all probability measures $Q$ on the domain of $P$ such that $Q$ and $P$ are progressively equivalent and…

Probability · Mathematics 2024-08-02 Spyridon M. Tzaninis , Nikolaos D. Macheras

In this paper, we study a class of multiscale McKean-Vlasov stochastic systems where the entire system depends on the distribution of the fast component. First of all, by the Poisson equation method we prove that the slow component…

Probability · Mathematics 2025-09-30 Jie Xiang , Huijie Qiao

The concept of statistical complexity is studied to characterize the classical kicked top model which plays important role in the qbit systems and the chaotic properties of the entanglement. This allows us to understand this driven…

Chaotic Dynamics · Physics 2020-11-18 Agnes Fülöp

In this note we study the optimal dividend problem for a company whose surplus process, in the absence of dividend payments, evolves as a generalized compound Poisson model in which the counting process is a generalized Poisson process.…

Pricing of Securities · Quantitative Finance 2014-02-26 Chuancun Yin

Poisson's equation plays a fundamental role as a tool for performance evaluation and optimization of Markov chains. For continuous-time birth-death chains with possibly unbounded transition and cost rates as addressed herein, when…

Probability · Mathematics 2022-07-28 José Niño-Mora

The two-parameter Poisson--Dirichlet distribution is a probability distribution on the totality of positive decreasing sequences with sum 1 and hence considered to govern masses of a random discrete distribution. A characterization of the…

Probability · Mathematics 2010-01-12 Kenji Handa

The classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then it is placed into the framework of evidence theory. Several authors like Laskey, Lehner (1989) and Provan (1990) already…

Artificial Intelligence · Computer Science 2013-03-08 Jurg Kohlas , Paul-Andre Monney

In many situations, the statistical properties of wave systems with chaotic classical limits are well-described by random matrix theory. However, applications of random matrix theory to scattering problems require introduction of system…

Statistical Mechanics · Physics 2013-05-29 James A. Hart , Thomas M. Antonsen , Edward Ott

We present a probabilistic model of events in continuous time in which each event triggers a Poisson process of successor events. The ensemble of observed events is thereby modeled as a superposition of Poisson processes. Efficient…

Machine Learning · Computer Science 2012-03-19 Aleksandr Simma , Michael I. Jordan

A family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributions, which includes some of the most frequently adopted…

Statistics Theory · Mathematics 2024-06-11 Antonio Di Noia , Marzia Marcheselli , Caterina Pisani , Luca Pratelli

A C++ class was written for the calculation of frequentist confidence intervals using the profile likelihood method. Seven combinations of Binomial, Gaussian, Poissonian and Binomial uncertainties are implemented. The package provides…

Data Analysis, Statistics and Probability · Physics 2010-01-21 J. Lundberg , J. Conrad , W. Rolke , A. Lopez

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Thorsten Glüsenkamp