26

Nonlinear Markov Networks for Continuous Variables
– Reimar Hofmann, Volker Tresp
 1998

3721

Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images
– S Geman, D Geman
 1984

1124

Graphical Models
– S L Lauritzen
 1996

1144

Spatial interaction and the statistical analysis of lattice systems (with Discussion
– Spatial statistics Besag, J
 1974

269

Statistical analysis of nonlattice data
– J E Besag
 1975

1

Markov chain sensitivity by mean first passage times
– G Cho
 1999

1

Markov chain sensitivity by mean rst passage times
– G Cho, C Meyer
 1999

1

Chaines doubles de Marko et fonctions aleatories de deux variables
– P Levy
 1948

1

stochastic systems. Statistical Science, 10, 3{66. Bayesian computation and
– C Bishop
 1995

1

On the distinction between the conditional probability and the joint probability approaches in the speci cation of nearestneighbor systems
– D
 1964

1

Markov chain sensitivity by mean rep
– G Cho, C Meyer
 1999

11

J.M.: Evaluating Logistic Models for Large Contingency Tables
– E B Fowlkes, A E Freeny, Landwehr
 1989

22

Does the Wakesleep Algorithm Produce Good Density Estimators?
– Brendan J. Frey, Geoffrey E. Hinton , Peter Dayan
 1996

7

Theory re nement onBayesian networks
– W Buntine
 1991

16

V.: Social class, parental encouragement, and educational aspirations
– W Sewell, Shah
 1968

20

Independence properties of directed Markov elds
– S Lauritzen, A Dawid, B Larsen, H Leimer
 1990

146

ªBayesian Updating in Recursive Graphical Models by Local Computations,º Computational Statistical Quarterly
– F V Jensen, S L Lauritzen, K G Olesen
 1990

15

On the distinction between the conditional probability and the joint probability approaches in the specification of nearestneighbour systems
– D BROOK
 1964

115

Bayesian computation and stochastic systems
– J BESAG, P J GREEN, D HIGDON, K MENGERSEN
 1995
