Thorngate, Warren and Edmonds, Bruce (2013) 'Measuring Simulation-Observation Fit: An Introduction to Ordinal Pattern Analysis'
Journal of Artificial Societies and Social Simulation 16 (2) 4 <
http://jasss.soc.surrey.ac.uk/16/2/4.html>.
Abstract
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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.
- Keywords:
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Ordinal, Goodness-Of-Fit, Statistics, Evidence, Validity, Predictions, Observations
Available at:
http://jasss.soc.surrey.ac.uk/16/2/4.html
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