The University of Southampton
University of Southampton Institutional Repository

Maximum Entropy, Parallel Computations and Lotteries

Maximum Entropy, Parallel Computations and Lotteries
Maximum Entropy, Parallel Computations and Lotteries
By picking unpopular sets of numbers in a lottery, it is possible to increase one’s expected winnings. We have used the Maximum Entropy method to estimate the probability of each of the 14 million tickets being chosen by players in the UK National Lottery. We discuss the parallel solution of the non-linear system of equations on a variety of platforms and give results which indicate the returns achieved by a syndicate buying a large number of tickets each week.
1252-8
Cox, S.J.
feea307f-f0e1-4063-869b-a3d0d947bfe2
Daniell, G.J.
f6ca2b4b-0ad9-4ae6-8cbe-97d6bffc899f
Nicole, D.A.
0aca6dd1-833f-4544-b7a4-58fb91c7395a
Cox, S.J.
feea307f-f0e1-4063-869b-a3d0d947bfe2
Daniell, G.J.
f6ca2b4b-0ad9-4ae6-8cbe-97d6bffc899f
Nicole, D.A.
0aca6dd1-833f-4544-b7a4-58fb91c7395a

Cox, S.J., Daniell, G.J. and Nicole, D.A. (1998) Maximum Entropy, Parallel Computations and Lotteries. Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications 1998 (PDPTA 1998). pp. 1252-8 .

Record type: Conference or Workshop Item (Paper)

Abstract

By picking unpopular sets of numbers in a lottery, it is possible to increase one’s expected winnings. We have used the Maximum Entropy method to estimate the probability of each of the 14 million tickets being chosen by players in the UK National Lottery. We discuss the parallel solution of the non-linear system of equations on a variety of platforms and give results which indicate the returns achieved by a syndicate buying a large number of tickets each week.

Text
paper05.pdf - Other
Download (41kB)

More information

Published date: 1998
Venue - Dates: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications 1998 (PDPTA 1998), 1998-01-01
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 250901
URI: http://eprints.soton.ac.uk/id/eprint/250901
PURE UUID: b1a24659-0ff3-4a32-a852-a151dbb25472

Catalogue record

Date deposited: 30 Sep 1999
Last modified: 14 Mar 2024 05:06

Export record

Contributors

Author: S.J. Cox
Author: G.J. Daniell
Author: D.A. Nicole

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×