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.
|Title of host publication||Dynamics & stochastics : Festschrift in honor of M.S. Keane|
|Editors||D. Denteneer, F. Hollander, den, E. Verbitskiy|
|Place of Publication||Beachwood OH, USA|
|Publisher||Institute for Mathematical Statistics|
|Publication status||Published - 2006|
|Name||Institute of Mathematical Statistics Lecture Notes - Monograph Series|