An overview of statistical decomposition techniques applied to complex systems

Date

2008-01-20

Author

Tuncer, Yalcin
Tanik, Murat M.
Allison, David B.

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The current state of the art in applied decomposition techniques is summarized within a comparative uniform framework. These techniques are classified by the parametric or information theoretic approaches they adopt. An underlying structural model common to all parametric approaches is outlined. The nature and premises of a typical information theoretic approach are stressed. Some possible application patterns for an information theoretic approach are illustrated. Composition is distinguished from decomposition by pointing out that the former is not a simple reversal of the latter. From the standpoint of application to complex systems, a general evaluation is provided.

Subject Keywords

Statistics and Probability, Computational Theory and Mathematics, Applied Mathematics, Computational Mathematics

URI

https://hdl.handle.net/11511/66351

Journal

COMPUTATIONAL STATISTICS & DATA ANALYSIS

DOI

https://doi.org/10.1016/j.csda.2007.09.012

Collections

Department of Statistics, Article

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Citation Formats

Y. Tuncer, M. M. Tanik, and D. B. Allison, “An overview of statistical decomposition techniques applied to complex systems,” COMPUTATIONAL STATISTICS & DATA ANALYSIS, pp. 2292–2310, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66351.