Symbolic Markov Chains

Monique Noirhomme Fraiture; Etienne Cuvelier

Symbolic Markov Chains

Monique Noirhomme Fraiture, Etienne Cuvelier

Faculty of Computer Science

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Chapter

90 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 language	English
Title of host publication	Selected Contributions in Data Analysis and Classification
Editors	Paula Brito, Patrice Bertr, Guy Cucumel, Francisco de
Pages	103-111
Number of pages	9
Publication status	Published - 2007

Access to Document

62978Submitted manuscript, 97.9 KB

Cite this

@inbook{00be171ac1cb48748b88e89388036053,

title = "Symbolic Markov Chains",

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.",

author = "Fraiture, {Monique Noirhomme} and Etienne Cuvelier",

note = "Publication editors : Paula Brito, Patrice Bertrand, Guy Cucumel, Francisco de Carvalho",

year = "2007",

language = "English",

pages = "103--111",

editor = "Paula Brito and Patrice Bertr and Guy Cucumel and Francisco de",

booktitle = "Selected Contributions in Data Analysis and Classification",

}

TY - CHAP

T1 - Symbolic Markov Chains

AU - Fraiture, Monique Noirhomme

AU - Cuvelier, Etienne

N1 - Publication editors : Paula Brito, Patrice Bertrand, Guy Cucumel, Francisco de Carvalho

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

M3 - Chapter

SP - 103

EP - 111

BT - Selected Contributions in Data Analysis and Classification

A2 - Brito, Paula

A2 - Bertr, Patrice

A2 - Cucumel, Guy

A2 - de, Francisco

ER -

Symbolic Markov Chains

Abstract

Access to Document

Fingerprint

Cite this