Markovian embeddings of general random strings

dc.creatorLladser, Manuel
dc.date2008-02-13
dc.date.accessioned2026-07-07T09:20:33Z
dc.date.available2026-07-07T09:20:33Z
dc.descriptionLet A be a finite set and X a sequence of A-valued random variables. We do not assume any particular correlation structure between these random variables; in particular, X may be a non-Markovian sequence. An adapted embedding of X is a sequence of the form R(X_1), R(X_1,X_2), R(X_1,X_2,X_3), etc where R is a transformation defined over finite length sequences. In this extended abstract we characterize a wide class of adapted embeddings of X that result in a first-order homogeneous Markov chain. We show that any transformation R has a unique coarsest refinement R' in this class such that R'(X_1), R'(X_1,X_2), R'(X_1,X_2,X_3), etc is Markovian. (By refinement we mean that R'(u)=R'(v) implies R(u)=R(v), and by coarsest refinement we mean that R' is a deterministic function of any other refinement of R in our class of transformations.) We propose a specific embedding that we denote as R^X which is particularly amenable for analyzing the occurrence of patterns described by regular expressions in X. A toy example of a non-Markovian sequence of 0's and 1's is analyzed thoroughly: discrete asymptotic distributions are established for the number of occurrences of a certain regular pattern in X_1,...,X_n, as n tends to infinity, whereas a Gaussian asymptotic distribution is shown to apply for another regular pattern.
dc.descriptionFull extended abstract available at http://www.siam.org/proceedings/analco/2008/analco08.php
dc.identifierhttps://arxiv.org/abs/0802.1896
dc.identifierhttp://arxiv.org/abs/0802.1896
dc.identifier2008 Proceedings of the Fourth Workshop on Analytic Algorithmics and Combinatorics (ANALCO)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/154756
dc.subjectProbability
dc.subjectCombinatorics
dc.subject68R15; 68Q45; 92D20
dc.titleMarkovian embeddings of general random strings
dc.typetext

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