文章基本信息

标题：Measuring Simulation-Observation Fit: An Introduction to Ordinal Pattern Analysis
本地全文：下载
作者：Warren Thorngate ; Bruce Edmonds
期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2013
卷号：16
期号：2
页码：1-16
DOI：10.18564/jasss.2139
出版社：University of Surrey, Department of Sociology
摘要：Most traditional strategies of assessing the fit between a simulation's set of predictions (outputs) and a set of relevant observations rely either on visual inspection or squared distances among averages. Here we introduce an alternative goodness-of-fit strategy, Ordinal Pattern Analysis (OPA) that will (we argue) be more appropriate for judging the goodness-of-fit of simulations in many situations. OPA is based on matches and mismatches among the ordinal properties of predictions and observations. It does not require predictions or observations to meet the requirements of interval or ratio measurement scales. In addition, OPA provides a means to assess prediction-observation fits case-by-case prior to aggregation, and to map domains of validity of competing simulations. We provide examples to illustrate how OPA can be employed to assess the ordinal fit and domains of validity of simulations of share prices, crime rates, and happiness ratings. We also provide a computer programme for assisting in the calculation of OPA indices.
关键词：Ordinal; Goodness-Of-Fit; Statistics; Evidence; Validity; Predictions; Observations