Markovianity in space and time

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dc.creatorvan Lieshout, M. N. M.
dc.date2006-08-10
dc.date.accessioned2026-07-07T08:08:06Z
dc.date.available2026-07-07T08:08:06Z
dc.description. Markov chains in time, such as simple random walks, are at the heart of probability. In space, due to the absence of an obvious definition of past and future, a range of definitions of Markovianity have been proposed. In this paper, after a brief review, we introduce a new concept of Markovianity that aims to combine spatial and temporal conditional independence.
dc.descriptionPublished at http://dx.doi.org/10.1214/074921706000000185 in the IMS Lecture Notes--Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0608242
dc.identifierhttp://arxiv.org/abs/math/0608242
dc.identifierIMS Lecture Notes--Monograph Series 2006, Vol. 48, 154-168
dc.identifierdoi:10.1214/074921706000000185
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131146
dc.subjectProbability
dc.subjectStatistics Theory
dc.subject60G55, 60D05 (Primary) 62M30 (Secondary)
dc.titleMarkovianity in space and time
dc.typetext

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