Symbolic Markov Chains

Monique Noirhomme Fraiture, Etienne Cuvelier

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter

78 Downloads (Pure)

Abstract

Stochastic processes have, since a long time, large applications in quite different domains. The standard theory considers discrete or continuous state space. We consider here the concept of Stochastic Process associated to all the cases of symbolic variables: quantitative, categorical single and multiple, interval, modal. More particularly, we adapt the definition of Markov Chain and give the equivalent of the Chapman-Kolmogorov theorem in all cases.
Original languageEnglish
Title of host publicationSelected Contributions in Data Analysis and Classification
EditorsPaula Brito, Patrice Bertr, Guy Cucumel, Francisco de
Pages103-111
Number of pages9
Publication statusPublished - 2007

Fingerprint Dive into the research topics of 'Symbolic Markov Chains'. Together they form a unique fingerprint.

Cite this