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In wireless networks, the knowledge of nodal distances is essential for several areas such as system configuration, performance analysis and protocol design. In order to evaluate distance distributions in random networks, the underlying…

Information Theory · Computer Science 2012-01-24 Sunil Srinivasa , Martin Haenggi

We are concerned with obtaining well-calibrated output distributions from regression models. Such distributions allow us to quantify the uncertainty that the model has regarding the predicted target value. We introduce the novel concept of…

Machine Learning · Statistics 2019-05-16 Hao Song , Tom Diethe , Meelis Kull , Peter Flach

This note aims at presenting several new theoretical results for the compound Poisson point process, which follows the work of Zhang \emph{et al.} [Insurance~Math.~Econom.~59(2014), 325-336]. The first part provides a new characterization…

Statistics Theory · Mathematics 2019-12-10 Huiming Zhang , Xiaoxu Wu

The goal of this paper is to analyze distributional Markov Decision Processes as a class of control problems in which the objective is to learn policies that steer the distribution of a cumulative reward toward a prescribed target law,…

Optimization and Control · Mathematics 2026-02-09 Nicole Bäuerle , Athanasios Vasileiadis

A discrete time branching process where the offspring distribution is generation-dependent, and the number of reproductive individuals is controlled by a random mechanism is considered. This model is a Markov chain but, in general, the…

Probability · Mathematics 2024-01-30 Miguel González , Carmen Minuesa , Manuel Mota , Inés del Puerto , Alfonso Ramos

1) We introduce random discrete Morse theory as a computational scheme to measure the complicatedness of a triangulation. The idea is to try to quantify the frequence of discrete Morse matchings with a certain number of critical cells. Our…

Computational Geometry · Computer Science 2014-04-21 Bruno Benedetti , Frank H. Lutz

A family of random probabilities is defined and studied. This family contains the Dirichlet process as a special case, corresponding to an inner point in the appropriate parameter space. The extension makes it possible to have random means…

Statistics Theory · Mathematics 2026-04-21 Nils Lid Hjort

In the derivation of Bell's inequalities, probability distribution is supposed to be a function of only hidden variable. We point out that the true implication of the probability distribution of Bell's correlation function is the…

General Physics · Physics 2020-07-21 Hai-Long Zhao

Recently the so-called Prabhakar generalization of the fractional Poisson counting process attracted much interest for his flexibility to adapt real world situations. In this renewal process the waiting times between events are IID…

Probability · Mathematics 2020-12-10 Thomas M. Michelitsch , Federico Polito , Alejandro P. Riascos

Bootstrapping was designed to randomly resample data from a fixed sample using Monte Carlo techniques. However, the original sample itself defines a discrete distribution. Convolutional methods are well suited for discrete distributions,…

Methodology · Statistics 2021-07-19 Jared M. Clark , Richard L. Warr

In this paper a randomized version of the Beverton-Holt type discrete model is proposed. Its solution stochastic process and the random steady state are determined. Its first probability density function and second probability density…

General Mathematics · Mathematics 2019-01-23 J. -C. Cortés , A. Navarro-Quiles , J. -V. Romero , M. -D. Roselló

This work considers the notion of random tensors and reviews some fundamental concepts in statistics when applied to a tensor based data or signal. In several engineering fields such as Communications, Signal Processing, Machine learning,…

Statistics Theory · Mathematics 2024-04-24 Divyanshu Pandey , Alexis Decurninge , Harry Leib

The generation of pseudo-random discrete probability distributions is of paramount importance for a wide range of stochastic simulations spanning from Monte Carlo methods to the random sampling of quantum states for investigations in…

Quantum Physics · Physics 2015-07-02 Jonas Maziero

The fractional Poisson process and the Wright process (as discretization of the stable subordinator) along with their diffusion limits play eminent roles in theory and simulation of fractional diffusion processes. Here we have analyzed…

Probability · Mathematics 2016-01-14 Rudolf Gorenflo , Francesco Mainardi

We develop an algorithm for computing bounded reachability probability for hybrid systems, i.e., the probability that the system reaches an unsafe region within a finite number of discrete transitions. In particular, we focus on hybrid…

Logic in Computer Science · Computer Science 2015-05-13 Fedor Shmarov , Paolo Zuliani

In this paper we introduce a new flexible class of distributions with bounded support, called reflected Generalized Topp-Leone Power Series (rGTL-PS), obtained by compounding the reflected Generalized Topp-Leone (van Drop and Kotz, 2006)…

Methodology · Statistics 2016-07-20 Francesca Condino , Filippo Domma

The number of extant individuals within a lineage, as exemplified by counts of species numbers across genera in a higher taxonomic category, is known to be a highly skewed distribution. Because the sublineages (such as genera in a clade)…

Applications · Statistics 2009-01-09 Panagis Moschopoulos , Max Shpak

We develop a systematic approach to establish Bell inequalities for qubits based on the Cauchy-Schwarz inequality. We also use the concept of distinct "roots" of Bell function to classify some well-known Bell inequalities for qubits. As…

Quantum Physics · Physics 2015-05-13 Jing-Ling Chen , Dong-Ling Deng

In this paper, we propose an extension of the Hawkes process by incorporating a kernel based on the tempered Mittag-Leffler distribution. This is the generalization of the work presented in [10]. We derive analytical results for the…

Probability · Mathematics 2024-08-22 Neha Gupta , Aditya Maheshwari

In this paper we develop a very general class of bivariate discrete distributions. The basic idea is very simple. The marginals are obtained by taking the random geometric sum of a baseline distribution function. The proposed class of…

Methodology · Statistics 2018-05-22 Debasis Kundu
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