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Related papers: Fully Analyzing an Algebraic Polya Urn Model

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One form of the inclusion-exclusion principle asserts that if A and B are functions of finite sets then A(S) is the sum of B(T) over all subsets T of S if and only if B(S) is the sum of (-1)^|S-T| A(T) over all subsets T of S. If we replace…

Combinatorics · Mathematics 2013-04-02 Ira M. Gessel

Interacting urns with exponential reinforcement were introduced and studied in Launay (2011). As its parameter $\rho$ tends to $\iy$, this reinforcement mechanism converges to the "generalized" reinforcement, in which the probability of…

Probability · Mathematics 2012-07-25 Mickaël Launay , Vlada Limic

In this paper we show how to extend the Sample-Path Large Deviation Principle for the urn model of Hill, Lane and Sudderth to the case in which the increment of the urn is not a binary variable. In particular, we sketch how to modify the…

Probability · Mathematics 2025-11-19 Simone Franchini

The probabilistic method is a technique for proving combinatorial existence results by means of showing that a randomly chosen object has the desired properties with positive probability. A particularly powerful probabilistic tool is the…

Combinatorics · Mathematics 2022-02-08 Anton Bernshteyn

We consider a model where a subset of candidates must be selected based on voter preferences, subject to general constraints that specify which subsets are feasible. This model generalizes committee elections with diversity constraints,…

Computer Science and Game Theory · Computer Science 2026-02-10 Piotr Skowron

The investigation of colour symmetries for periodic and aperiodic systems consists of two steps. The first concerns the computation of the possible numbers of colours and is mainly combinatorial in nature. The second is algebraic and…

Disordered Systems and Neural Networks · Physics 2007-05-23 Michael Baake , Uwe Grimm , Max Scheffer

In the apportionment problem, a fixed number of seats must be distributed among parties in proportion to the number of voters supporting each party. We study a generalization of this setting, in which voters can support multiple parties by…

Computer Science and Game Theory · Computer Science 2022-03-31 Markus Brill , Paul Gölz , Dominik Peters , Ulrike Schmidt-Kraepelin , Kai Wilker

Consider throwing $n$ balls at random into $m$ urns, each ball landing in urn $i$ with probability $p_i$. Let $S$ be the resulting number of singletons, i.e., urns containing just one ball. We give an error bound for the Kolmogorov distance…

Probability · Mathematics 2009-01-23 Mathew D. Penrose

We consider systems of interacting Generalized Friedman's Urns (GFUs) having irreducible mean replacement matrices. The interaction is modeled through the probability to sample the colors from each urn, that is defined as convex combination…

Probability · Mathematics 2018-01-09 Giacomo Aletti , Andrea Ghiglietti

We consider weighted negatively reinforced urn schemes with finitely many colours. An urn scheme is called negatively reinforced, if the selection probability for a colour is proportional to the weight $w$ of the colour proportion, where…

Probability · Mathematics 2019-05-28 Gursharn Kaur

Generalized probability distributions for Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac statistics, with unequal source probabilities $q_i$ for each level $i$, are obtained by combinatorial reasoning. For equiprobable degenerate…

Statistical Mechanics · Physics 2008-08-18 Robert K. Niven , Marian Grendar

Various forms of sorting problems have been studied over the years. Recently, two kinds of sorting puzzle apps are popularized. In these puzzles, we are given a set of bins filled with colored units, balls or water, and some empty bins.…

We introduce a dynamic generative model, Bayesian allocation model (BAM), which establishes explicit connections between nonnegative tensor factorization (NTF), graphical models of discrete probability distributions and their Bayesian…

Machine Learning · Statistics 2019-03-12 Ali Taylan Cemgil , Mehmet Burak Kurutmaz , Sinan Yildirim , Melih Barsbey , Umut Simsekli

We introduce a multi-colour multi-urn generalisation of the Bernoulli-Laplace urn model, consisting of $d$ urns, $m$ colours, and $dmn$ balls, with $dn$ balls of each colour and $mn$ balls in each urn. At each step, one ball is drawn…

Probability · Mathematics 2025-11-14 Ritesh Goenka , Jonathan Hermon , Dominik Schmid

Polya Enumeration Theorem is one of the most useful tools dealing with the enumeration of patterns that are symmetric in some ways. What follows is a procedure for obtaining the results of Polya Theorem directly, bypassing the usual…

History and Overview · Mathematics 2010-01-05 Kung-Wei Yang

An urn contains black and red balls. Let $Z_n$ be the proportion of black balls at time $n$ and $0\leq L<U\leq 1$ random barriers. At each time $n$, a ball $b_n$ is drawn. If $b_n$ is black and $Z_{n-1}<U$, then $b_n$ is replaced together…

Probability · Mathematics 2015-08-27 Patrizia Berti , Irene Crimaldi , Luca Pratelli , Pietro Rigo

We consider multicolor urn models with multiple drawings. An urn model is called linear if the conditional expected value of the urn composition at time $n$ is a linear function of the composition at time $n-1$. For four different sampling…

Probability · Mathematics 2016-12-14 Markus Kuba

This paper presents DiffSum, a simple post-election risk-limiting ballot-polling audit for two-candidate plurality elections. DiffSum sequentially draws ballots (without replacement) until the numbers $a$, $b$, of votes for candidates $A$,…

Computers and Society · Computer Science 2015-09-02 Ronald L. Rivest

An urn scheme is a probabilistic model in which balls are placed into urns sequentially and independently of each other. All balls share the same probability distribution for hitting the urns. In the simplest case, there is a finite number…

Probability · Mathematics 2026-02-17 Berhane Abebe , Mikhail Chebunin , Artyom Kovalevskii

We begin by reviewing some probabilistic results about the Dirichlet Process and its close relatives, focussing on their implications for statistical modelling and analysis. We then introduce a class of simple mixture models in which…

Methodology · Statistics 2010-03-23 Peter J. Green
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