A percolating state selector for suffix-tree context models

This paper introduces into practice and empirically evaluates a set of techniques for information-theoretic state selection that have been developing in asymptotic results state selection, which actually implements the selection of an entire model from among a set of competing models, is performed at least trivially by all of the suffix-tree FSMs used for on-line probability estimation. The set of state-selection techniques presented combines orthogonally with the other sets of design options covered in the companion paper of Bunton (Proceedings Data Compression Conference, p.42, 1997).