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In this paper, we generalize the recently studied Stochastic Matching problem to more accurately model a significant medical process, kidney exchange, and several other applications. Up until now the Stochastic Matching problem that has…

Data Structures and Algorithms · Computer Science 2022-05-31 Alireza Farhadi , Jacob Gilbert , MohammadTaghi Hajiaghayi

We generalize Taylor's theorem by introducing a stochastic formulation based on an underlying Poisson point process model. We utilize this approach to propose a novel non-linear regression framework and perform statistical inference of the…

Methodology · Statistics 2025-08-07 Weichao Wu , Athanasios C. Micheas

Many statistical problems involve mixture models and the need for computationally efficient methods to estimate the mixing distribution has increased dramatically in recent years. Newton [Sankhya Ser. A 64 (2002) 306--322] proposed a fast…

Methodology · Statistics 2011-02-18 Ryan Martin , Jayanta K. Ghosh

Stacy distribution defined for the first time in 1961 provides a flexible framework for modelling of a wide range of real-life behaviours. It appears under different names in the scientific literature and contains many useful particular…

Probability · Mathematics 2023-03-21 Pavlina K. Jordanova , Mladen Savov , Assen Tchorbadjieff , Milan Stehlík

In this paper, an alternative mixed Poisson distribution is proposed by amalgamating Poisson distribution and a modification of the Quasi Lindley distribution. Some fundamental structural properties of the new distribution, namely the shape…

Methodology · Statistics 2021-10-26 Ramajeyam Tharshan , Pushpakanthie Wijekoon

A Poisson or a binomial process on an abstract state space and a symmetric function $f$ acting on $k$-tuples of its points are considered. They induce a point process on the target space of $f$. The main result is a functional limit theorem…

Probability · Mathematics 2016-06-07 Laurent Decreusefond , Matthias Schulte , Christoph Thäle

In this note we discuss additional properties of mixed Poisson distributions. We discuss the convergence of mixed Poisson distributions to its mixing distribution for the scaling parameter tending to infinity. Moreover, we obtain a central…

Probability · Mathematics 2025-02-13 Markus Kuba

We propose in this paper a new coding scheme called twisted-pair superposition transmission (TPST). The encoding is to "mix together" a pair of basic codes by superposition, while the decoding can be implemented as a successive cancellation…

Information Theory · Computer Science 2021-01-25 Suihua Cai , Xiao Ma

The paper provides a simpler method for proving a delicate inequality that was used by Achlioptis and Naor to establish asymptotic concentration for chromatic numbers of Erdos-Renyi random graphs. The simplifications come from two new…

Discrete Mathematics · Computer Science 2011-07-20 John Hartigan , David Pollard , Sekhar Tatikonda

We present improved numerical approximations to the exact Poissonian confidence limits for small numbers n of observed events following the approach of Gehrels (1986). Analytic descriptions of all parameters used in the approximations are…

Astrophysics · Physics 2009-11-07 Harald Ebeling

We provide a general theorem bounding the error in the approximation of a random measure of interest--for example, the empirical population measure of types in a Wright-Fisher model--and a Dirichlet process, which is a measure having…

Probability · Mathematics 2020-07-07 Han L. Gan , Nathan Ross

Least-squares fits are an important tool in many data analysis applications. In this paper, we review theoretical results, which are relevant for their application to data from counting experiments. Using a simple example, we illustrate the…

Data Analysis, Statistics and Probability · Physics 2019-06-07 Hans Dembinski , Michael Schmelling , Roland Waldi

Addressing the challenge of scaling-up epidemiological inference to complex and heterogeneous models, we introduce Poisson Approximate Likelihood (PAL) methods. In contrast to the popular ODE approach to compartmental modelling, in which a…

Methodology · Statistics 2023-06-05 Michael Whitehouse , Nick Whiteley , Lorenzo Rimella

Consider a measure $\mu_\lambda = \sum_x \xi_x \delta_x$ where the sum is over points $x$ of a Poisson point process of intensity $\lambda$ on a bounded region in $d$-space, and $\xi_x$ is a functional determined by the Poisson points near…

Probability · Mathematics 2013-02-05 Mathew D. Penrose , Andrew R. Wade

This document is due to appear as a chapter of the forthcoming Handbook of Approximate Bayesian Computation (ABC) by S. Sisson, L. Fan, and M. Beaumont. Here we describe some of the circumstances under which statistical ecologists might…

Methodology · Statistics 2015-11-10 Matteo Fasiolo , Simon N. Wood

In pump-probe spectroscopy, one often needs to analyse the transmission or reflection of electromagnetic waves through optically pumped media. Here, it is common practice to approximate the analysis in order to extract non-equilibrium…

Optics · Physics 2019-02-26 Peter Karlsen , Euan Hendry

This paper establishes expectation and variance asymptotics for statistics of the Poisson--Voronoi approximation of general sets, as the underlying intensity of the Poisson point process tends to infinity. Statistics of interest include…

Probability · Mathematics 2016-06-24 Christoph Thäle , J. E. Yukich

The article determines the asymptotic shape of the extremal clusters in stationary regularly varying random fields. To deduce this result, we present a general framework for the Poisson approximation of point processes on Polish spaces…

Probability · Mathematics 2020-09-22 Bojan Basrak , Hrvoje Planinić

The Traveling Salesman Problem (TSP) is a classic and extensively studied problem with numerous real-world applications in artificial intelligence and operations research. It is well-known that TSP admits a constant approximation ratio on…

Data Structures and Algorithms · Computer Science 2025-12-02 Jingyang Zhao , Zimo Sheng , Mingyu Xiao

This paper addresses the mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multi-object posterior density of the map given a set of measurements. The landmarks in the map are modeled as extended objects,…

Machine Learning · Statistics 2018-11-09 Maryam Fatemi , Karl Granström , Lennart Svensson , Francisco J. R. Ruiz , Lars Hammarstrand