CMU-ISRI-04-136Institute for Software Research International School of Computer Science, Carnegie Mellon University
CMU-ISRI-04-136
Kathleen M. Carley, Natalia Y. Kamneva, Jeff Reminga October 2004
Institute for Software Research International (ISRI)
CMU-ISRI-04-136.ps
Keywords: Response Surface Methodology (RSM), regression analysis,
linear regression model, regressors, variable selection, model building,
full model, multicollinearity, ridge regression, unit length scaling,
condition number, optimization, simulated annealing, global optimum
In Social Network Problems usually the underlying mechanism is not
fully understood, and the experimenter must approximate the unknown
function ε represents the error in the system.
Usually the function Identifying and fitting from experimental data an appropriate response surface model requires some use of statistical experimental design fundamentals, regression modeling techniques, and optimization methods. All three of these topics are usually combined into Response Surface Methodology (RSM). Also the experimenter may encounter situations where the full model may not be appropriate. Then variable selection or model-building techniques may be used to identify the best subset of regressors to include in a regression model. In our approach we use the simulated annealing method of optimization for searching the best subset of regressors. In some response surface experiments, there can be one or more near-linear dependences among regressor variables in the model. Regression model builders refer to this as multicollinearity among the regressors. Multicollinearity can have serious effects on the estimates of the model parameters and on the general applicability of the final model. The RSM is also extremely useful as an automated tool for model calibration and validation especially for modern computational multi-agent large-scale social-networks systems that are becoming heavily used in modeling and simulation of complex social networks. The RSM can be integrated in many large-scale simulation systems such as BioWar, ORA and is currently integrating in Vista, Construct, and DyNet. This report describes the theoretical approach for solving of these problems and the implementation of chosen methods. 31 pages
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