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Episciences
Article . 2022
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Compositionality
Article . 2022 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2021
License: CC BY
Data sources: Datacite
DBLP
Article . 2022
Data sources: DBLP
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Urns & Tubes

Authors: Bart Jacobs 0001;
Abstract

Urn models play an important role to express various basic ideas in probability theory. Here we extend this urn model with tubes. An urn contains coloured balls, which can be drawn with probabilities proportional to the numbers of balls of each colour. For each colour a tube is assumed. These tubes have different sizes (lengths). The idea is that after drawing a ball from the urn it is dropped in the tube of the corresponding colour. We consider two associated probability distributions. The first-full distribution on colours gives for each colour the probability that the corresponding tube is full first, before any of the other tubes. The negative distribution on natural numbers captures for a numberkthe probability that all tubes are full for the first time afterkdraws.This paper uses multisets to systematically describe these first-full and negative distributions in the urns and tubes setting, in fully multivariate form, for all three standard drawing modes (multinomial, hypergeometric, and Pólya).

Keywords

Probability (math.PR), FOS: Mathematics, G.3, Mathematics - Probability, 60A05

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
gold