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This paper revisits the problem of computing empirical cumulative distribution functions (ECDF) efficiently on large, multivariate datasets. Computing an ECDF at one evaluation point requires $\mathcal{O}(N)$ operations on a dataset…

Data Structures and Algorithms · Computer Science 2021-09-21 Nicolas Langrené , Xavier Warin

We derive a stochastic partial differential equation that describes the fluctuating behaviour of reaction-diffusion systems of N particles, undergoing Markovian, unary reactions. This generalises the work of Dean [J. Phys. A: Math. and…

Statistical Mechanics · Physics 2025-01-13 Richard E. Spinney , Richard G. Morris

In this letter, we characterize the distribution of the number of users associated with the typical base station (BS), termed the typical cell load, in a cellular network where the BSs are distributed as a homogeneous Poisson point process…

Information Theory · Computer Science 2020-04-22 Chiranjib Saha , Harpreet S. Dhillon

Despite the fundamental nature of the inhomogeneous Poisson process in the theory and application of stochastic processes, and its attractive generalizations (e.g. Cox process), few tractable nonparametric modeling approaches of intensity…

Machine Learning · Statistics 2017-06-27 Seth Flaxman , Yee Whye Teh , Dino Sejdinovic

Poisson point processes provide a versatile framework for modeling the distributions of random points in space. When the space is partitioned into cells, each associated with a single generating point from the Poisson process, there appears…

Numerical Analysis · Mathematics 2024-05-14 Jaume Anguera Peris , Joakim Jaldén

The object of this paper is to study and develop a Poisson distribution in generalized Wright function form.

Probability · Mathematics 2024-10-22 Dharmendra Kumar Singh

The paper develops new methods of non-parametric estimation a compound Poisson distribution. Such a problem arise, in particular, in the inference of a Levy process recorded at equidistant time intervals. Our key estimator is based on…

Statistics Theory · Mathematics 2015-10-19 Alexey Lindo , Sergei Zuyev , Serik Sagitov

The concentration of empirical measures is studied for dependent data, whose joint distribution satisfies Poincar\'{e}-type or logarithmic Sobolev inequalities. The general concentration results are then applied to spectral empirical…

Statistics Theory · Mathematics 2010-11-30 S. G. Bobkov , F. Götze

We investigate the fluctuations around the mean of the Stieltjes transform of the empirical spectral distribution of any selfadjoint noncommutative polynomial in a Wigner matrix and a deterministic diagonal matrix. We obtain the convergence…

Probability · Mathematics 2021-07-22 Serban Belinschi , Mireille Capitaine , Sandrine Dallaporta , Maxime Fevrier

We want to approximate general multivariate probability density functions by deterministic sample sets. For optimal sampling, the closeness to the given continuous density has to be assessed. This is a difficult challenge in multivariate…

Systems and Control · Electrical Eng. & Systems 2020-01-01 Uwe D. Hanebeck

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner's generalized Dirichlet distribution (R.H. Lochner, A Generalized…

Mathematical Physics · Physics 2013-10-02 J. Bakosi , J. R. Ristorcelli

Any empirical data can be approximated to one of Pearson distributions using the first four moments of the data (Elderton and Johnson, 1969; Pearson, 1895; Solomon and Stephens, 1978). Thus, Pearson distributions made statistical analysis…

Computation · Statistics 2019-12-24 Wei Pan , Xinming An , Qing Yang

We introduce a mltiparameter version of Skellam point process via multiparameter Poisson processes. Its distributional properties are studied in detail. Its compound representation is derived for a particular case. Also, its Riemann…

Probability · Mathematics 2025-09-17 Pradeep Vishwakarma

Application of root density estimator to problems of statistical data analysis is demonstrated. Four sets of basis functions based on Chebyshev-Hermite, Laguerre, Kravchuk and Charlier polynomials are considered. The sets may be used for…

Quantum Physics · Physics 2015-06-23 Yu. I. Bogdanov , N. A. Bogdanova

Consider a graph on randomly scattered points in an arbitrary space, with two points $x,y$ connected with probability $\phi(x,y)$. Suppose the number of points is large but the mean number of isolated points is $O(1)$. We give general…

Probability · Mathematics 2017-09-21 Mathew D. Penrose

This paper presents and examines computationally convenient goodness-of-fit tests for the family of generalized Poisson distributions, which encompasses notable distributions such as the Compound Poisson and the Katz distributions. The…

Methodology · Statistics 2024-11-21 A. Batsidis , B. Milošević , M. D. Jiménez-Gamero

In this work, we study the partial sums of independent and identically distributed random variables with the number of terms following a fractional Poisson (FP) distribution. The FP sum contains the Poisson and geometric summations as…

Statistics Theory · Mathematics 2021-04-01 Gabriela Oliveira , Wagner Barreto-Souza , Roger W. C. Silva

In the paper we suggest a new construction of stochastic flows of kernels in a locally compact separable metric space $M$. Starting from a consistent sequence of Feller transtition function $(\mathsf{P}^{(n)}: n\geq 1)$ on $M$ we prove…

Probability · Mathematics 2025-01-07 Georgii Riabov

In this paper we propose a generalized Gaussian process concurrent regression model for functional data where the functional response variable has a binomial, Poisson or other non-Gaussian distribution from an exponential family while the…

Methodology · Statistics 2014-02-03 Bo Wang , Jian Qing Shi

Husimi distribution function for the one-dimensional Ising model is obtained. One-point and joint distribution functions are calculated and their thermal behaviour are discussed.

Quantum Physics · Physics 2007-05-23 F. Kheirandish
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