Abstract
Two features are commonly observed in large and complex systems. First, a system is made up of multiple subsystems. Second there exists fragmented data. A methodological challenge is to reconcile the potential parametric inconsistency across individually calibrated subsystems. This study aims to explore a novel approach, called system-subsystem dependency network, which is capable of integrating subsystems that have been individually calibrated using separate data sets. In this paper we compare several techniques for solving the methodological challenge. Additionally, we use data from a large-scale epidemiologic study as well as a large clinical trial to illustrate the solution to inconsistency of overlapping subsystems and the integration of data sets.
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Ip, E.H., Chen, SH., Rejeski, J. (2014). System-Subsystem Dependency Network for Integrating Multicomponent Data and Application to Health Sciences. In: Kennedy, W.G., Agarwal, N., Yang, S.J. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2014. Lecture Notes in Computer Science, vol 8393. Springer, Cham. https://doi.org/10.1007/978-3-319-05579-4_8
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DOI: https://doi.org/10.1007/978-3-319-05579-4_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05578-7
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