PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Markovianity in space and time
Marie-Colette van Lieshout
In: Dynamics & Stochastics: Festschrift in honour of M.S. Keane Lecture Notes - Monograph Series , 48 . (2006) Institute for Mathematical Statistics , Beachwood, USA , pp. 154-168.

Abstract

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.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:2396
Deposited By:Marie-Colette van Lieshout
Deposited On:22 November 2006