Labelled graphical models

Scandinavian Journal of Statistics

Volumn 30, Issue 3, 2003, Pages 493-508

  Corander, Jukka ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

Author keywords

Bayesian model determination; Graphical models; Log linear models; Reference analysis; Utility

Indexed keywords

EID: 0042362226     PISSN: 03036898     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9469.00344     Document Type: Article

References (30)

1. Barndorff-Nielsen, O. E. (1978). Information and exponential families in statistical theory. Wiley, New York.
2. Bock, H.-H. (1986). Loglinear models and entropy clustering methods for qualitative data. In Classification as a tool of research (eds W. Gaul & M. Schader), 19-26. North-Holland, Amsterdam.
3. Bock, H.-H. (1994). Information and entropy in cluster analysis. In Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: an informational approach (ed. H. Bozdogan), 115-147. Kluwer, Amsterdam.
4. Bock, H.-H. (1996). Probability models and hypothesis testing in partitioning cluster analysis. In Clustering and classification (eds P. Arabie, L. Hubert & G. De Soete), 377-453. World Scientific, River Edge.
5. Brown, L. (1986). Fundamentals of statistical exponential families. Institute of Mathematical Statistics, Hayward.
6. Corander, J. (2003). Bayesian graphical model determination using decision theory. J. Multivariate Anal., in press.
7. Csiszar, I. (1975). I-divergence geometry of probability distributions and minimization problems. Ann. Probab. 3, 146-158.
8. Darroch, J., Lauritzen, S. L. & Speed, T. (1980). Markov fields and log-linear interaction models for contingency tables. Ann. Statist. 8, 522-539.
9. Dawid, A. P. & Lauritzen, S. L. (1993). Hyper-Markov laws in the statistical analysis of decomposable graphical models. Ann. Statist. 21, 1272-1317.
10. Dellaportas, P. & Forster, J. J. (1999). Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models. Biometrika, 86, 615-633.
11. Edwards, D. (2000). Introduction to graphical modelling. Springer-Verlag, New York.
12. Eriksen, P. S. (1999). Context specific interaction models. Technical report, available at www.math.auc.dk/research/reports/.
13. Fowlkes, E. B., Freeny, A. E. & Landwehr, J. M. (1988). Evaluating logistic models for large contingency tables. J. Amer. Statist. Assoc. 83, 611-622.
14. Giudici, P. & Green, P. J. (1999). Decomposable graphical Gaussian model determination. Biometrika 86, 785-801.
15. Giudici, P., Green, P. J. & Tarantola, C. (1999). Efficient model determination for discrete graphical models. Technical report, available at www.statslab.cam.ac.uk/MCMC/.
16. Hannan, E. & Quinn, B. (1979). The determination of the order of an autoregression. J. R. Stat. Soc. Ser B Stat. Methodol. 41, 190-195.
17. Højsgaard, S. (1998). Split models for contingency tables. PhD Thesis. Danish Institute of Agricultural Science, Biometry Research Unit, Tjele, Denmark.
18. Højsgaard, S. (2003a). Statistical inference in context specific interaction models for contingency tables. Accepted for publication in Scand J Statist.
19. Højsgaard, S. (2003b). Split models for contingency tables. Comput. Statist. Data Anal., in press
20. Lauritzen, S. L. (1996). Graphical models. Oxford University Press, Oxford.
21. Madigan, D. & Raftery, A. E. (1994). Model selection and accounting for model uncertainty in graphical models using Occam's window. J. Amer. Statist. Assoc. 89, 1535-1546.
22. Madigan, D. & York, J. (1995). Bayesian graphical models for discrete data. Int. Statist. Rev., 63, 215-232.
23. Malvestuto, F. M. (1996). Testing implication of hierarchical log-linear models for probability distributions. Statist. Comput. 6, 169-176.
24. Myllymäki, P., Silander, T., Tirri, H. & Uronen, P. (2001). Bayesian data mining on the Web with B-Course. In Proceedings of the 2001 IEEE International Conference on Data Mining (eds N. Cereone, T. Y. Lin & X. Wu), 626-629. IEEE Computer Society Press.
25. Rudas, T. (1998). A new algorithm for the maximum likelihood estimation of graphical log-linear models. Comput. Statist. 13, 529-537.
26. Schwarz, G. (1978). Estimating the dimension of a model. Ann. Statist. 6, 461-464.
27. Teugels, J. & Van Horebeek, (1998a). Generalized graphical models for discrete data. Statist. Probab. Lett. 38, 41-47.
28. Teugels, J. & Van Horebeek, (1998b). Algebraic descriptions of nominal multivariate discrete data. J. Multivariate Anal. 67, 203-226.
29. Whittaker, J. (1990). Graphical models in applied multivariate statistics. Wiley, Chichester.
30. Yuan, L. & Kesavan, H. (1997). Bayesian estimation of Shannon entropy. Comm. Statist. Theory Methods 26, 139-148.