Title
Discovering metamodels' quality-of-fit for simulation via graphical techniques
Abstract
Metamodels are used in many disciplines to replace simulation models of complex multivariate systems. To discover metamodels ‘quality-of-fit’ for simulation, simple information returned by average-based statistics, such as root-mean-square error RMSE, are often used. The sample of points used in determining these averages is restricted in size, especially for simulation models of complex multivariate systems. Obviously, decisions made based on average values can be misleading when the sample size is not adequate, and contributions made by each individual data point in such samples need to be examined. This paper presents methods that can be used to discover metamodels quality-of-fit graphically by means of two-dimensional plots. Three plot types are presented; these are the so-called circle plots, marksman plots, and ordinal plots. Such plots can be used to facilitate visual inspection of the effect on metamodel accuracy of each individual point in the data sample used for metamodel validation. The proposed methods can be used to complement quantitative validation statistics; in particular, for situations where there is not enough validation data or the validation data is too expensive to generate.
Year
DOI
Venue
2007
10.1016/j.ejor.2006.01.026
European Journal of Operational Research
Keywords
Field
DocType
Simulation,Modeling,Metamodel validation
Data mining,Mathematical optimization,Visual inspection,Sample (statistics),Multivariate statistics,Computer science,Mean squared error,Simulation modeling,Statistical graphics,Statistics,Sample size determination,Metamodeling
Journal
Volume
Issue
ISSN
178
2
0377-2217
Citations 
PageRank 
References 
3
0.48
5
Authors
2
Name
Order
Citations
PageRank
Husam Hamad1122.81
Sami Al-Hamdan261.42