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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao zbMATH Openarrow_drop_down
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Article
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Advances in Applied Probability
Article . 1978 . Peer-reviewed
Data sources: Crossref
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Unilateral Ising Models

Unilateral Ising models
Authors: Pickard, David K.;

Unilateral Ising Models

Abstract

Ising lattices model spatial interaction among binary variables, and consequently, are relevant to many scientific disciplines. They are intuitively appealing models because their conditional distributions are given locally (they are Markov fields). On the other hand, their marginal distributions (even for pairs of sites, let alone triples, etc.) are relatively intractable. Indeed, even for the simplest Ising model it is remarkably difficult to obtain the correlation structure (cf. Kaufmann and Onsager (1949), Hurst and Green (1960)). Furthermore, general Ising models are not amenable to direct simulation. Recently, a number of articles have appeared which consider rather specialized binary lattice processes (cf. Bartlett (1967), Besag (1972), Welberry and Galbraith (1973), (1975), Galbraith and Walley (1976), Welberry (1977), Verhagen (1978), Enting (1977), Pickard (1977a)). These models admit direct simulation and have relatively simple marginals. For the most part, however, this work has been rather fragmentary and heuristic. The purpose of the present paper is to report briefly the beginnings of a unified theory (Pickard (1977b)). Proofs are omitted as there is insufficient space. A more detailed account will appear elsewhere.

Keywords

Stationary Field, Random Spin System, Interacting random processes; statistical mechanics type models; percolation theory, Jsing Models, Pair Correlation Function

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Top 10%
Average
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