Jump to ContentJump to Main Navigation
Party CompetitionAn Agent-Based Model$
Users without a subscription are not able to see the full content.

Michael Laver and Ernest Sergenti

Print publication date: 2011

Print ISBN-13: 9780691139036

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691139036.001.0001

Show Summary Details
Page of

PRINTED FROM PRINCETON SCHOLARSHIP ONLINE (www.princeton.universitypressscholarship.com). (c) Copyright Princeton University Press, 2017. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in HSO for personal use (for details see http://www.universitypressscholarship.com/page/privacy-policy).date: 10 December 2017

Systematically Interrogating Agent-Based Models

Systematically Interrogating Agent-Based Models

Chapter:
(p.56) Chapter Four Systematically Interrogating Agent-Based Models
Source:
Party Competition
Author(s):

Michael Laver

Ernest Sergenti

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691139036.003.0004

This chapter develops the methods for designing, executing, and analyzing large suites of computer simulations that generate stable and replicable results. It starts with a discussion of the different methods of experimental design, such as grid sweeping and Monte Carlo parameterization. Next, it demonstrates how to calculate mean estimates of output variables of interest. It does so by first discussing stochastic processes, Markov Chain representations, and model burn-in. It focuses on three stochastic process representations: nonergodic deterministic processes that converge on a single state; nondeterministic stochastic processes for which a time average provides a representative estimate of the output variables; and nondeterministic stochastic processes for which a time average does not provide a representative estimate of the output variables. The estimation strategy employed depends on which stochastic process the simulation follows. Lastly, the chapter presents a set of diagnostic checks used to establish an appropriate sample size for the estimation of the means.

Keywords:   computer simulation, grid sweeping, Monte Carlo parameterization, stochastic processes, agent-based models

Princeton Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us.