Published In
Kybernetes
Document Type
Post-Print
Publication Date
2004
Subjects
Reconstructability Analysis, Information Theory, Probabilistic graphical modeling, Multivariate analysis discrete multivariate modeling, Data mining
Abstract
Reconstructability analysis (RA) is a method for detecting and analyzing the structure of multivariate categorical data. While Jones and his colleagues extended the original variable‐based formulation of RA to encompass models defined in terms of system states, their focus was the analysis and approximation of real‐valued functions. In this paper, we separate two ideas that Jones had merged together: the “g to k” transformation and state‐based modeling. We relate the idea of state‐based modeling to established variable‐based RA concepts and methods, including structure lattices, search strategies, metrics of model quality, and the statistical evaluation of model fit for analyses based on sample data. We also discuss the interpretation of state‐based modeling results for both neutral and directed systems, and address the practical question of how state‐based approaches can be used in conjunction with established variable‐based methods.
DOI
10.1108/03684920410534092
Persistent Identifier
http://archives.pdx.edu/ds/psu/16505
Citation Details
Zwick, M., and Johnson, M. S. (2004). "State-Based Reconstructability Analysis." Kybernetes, vol. 33, No. 5/6, pp. 1041-1052.
Description
Authors' version of an article which subsequently appeared in Kybernetes, published by Emerald Group Publishing Limited. The version of record may be found at http://dx.doi.org/10.1108/03684920410534092.