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A Practical Guide for the Creation of Random Number Sequences from Aggregated Correlation Data for Multi-Agent Simulations
Author(s) -
Volker Nissen,
Danilo Saft
Publication year - 2014
Publication title -
journal of artificial societies and social simulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.768
H-Index - 59
ISSN - 1460-7425
DOI - 10.18564/jasss.2593
Subject(s) - correlation , computer science , statistical physics , mathematics , physics , geometry
This article describes a scalable way to initialise a simulation model with correlated random numbers. The focus is on the nontrivial issue of creating predefined multidimensional correlations amongst those numbers. A multi-agent model serves as a basis for practical demonstrations in this paper, while the method itself is interesting for an even wider audience within the modelling and simulation community beyond the field of agent-based modelling. In particular, we demonstrate how streams of correlated random numbers for different empirically-based model parameters can be generated when just given aggregated statistics in the form of a correlation matrix. An example initialisation procedure is demonstrated using the open source statistical computing software "R" as well as the open source multi-agent simulation software "Repast Simphony". We also provide a digression for NetLogo users.

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