Mixed Markov models

Proceedings of the National Academy of Sciences of the United States of America

Volumn 100, Issue 14, 2003, Pages 8092-8096

  Fridman, Arthur ^a  

^a MERCK RESEARCH LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; CALCULATION; GLOBAL CHANGE; PRIORITY JOURNAL; PROBABILITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; THEORETICAL MODEL;

EID: 0038492647     PISSN: 00278424     EISSN: None     Source Type: Journal    
DOI: 10.1073/pnas.0731829100     Document Type: Article

References (16)

1. Kindermann, R. & Snell, J. (1980) Markov Random Fields and Their Applications (Amer. Math. Soc., Providence, RI).
2. Jensen, F. (1996) An Introduction to Bayesian Networks (University College Press, London).
3. Smyth, P. (1997) Pattern Recognit. Lett. 18, 1261-1268.
4. Hasty, J., McMillen, D., Isaacs, F. & Collins, J. (2001) Nat. Genetics 2, 268-279.
5. Mumford, D. (1996) in ICIAM 95, eds. Kirchgassner, K., Mahrenholtz, O. & Mennicken, R. (Akademie Verlag, Berlin), pp. 233-256.
6. Mumford, D. (1997) in The Legacy of Norbert Wiener: A Centennial Symposium, eds. Jerison, D., Singer, I. & Stroock, D. (Amer. Math. Soc., Providence, RI), pp. 235-260.
7. Winkler, G. (1995) Image Analysis, Random Fields and Dynamic Monte Carlo Methods (Springer, Berlin).
8. Hammersley, J. & Clifford, P. (1968) Markov Fields on Finite Graphs and Lattices, preprint.
9. Grimmett, G. (1973) Bull. Lond. Math. Soc. 5, 81-84.
10. Geiger, D. & Heckerman, D. (1996) Artificial Intelligence 82, 45-74.
11. Lauritzen, S. (1996) Graphical Models (Clarendon, Oxford).
12. Geman, S. & Geman, D. (1984) IEEE Trans. Pattern Anal. Machine Intell. 6, 721-741.
13. Besag, J. (1986) J. R. Stat. Soc. B 48, 259-302.
14. Fischler, M. & Elschlager, R. (1973) IEEE Trans. Computers 22, 67-92.
15. Yuille, A. (1990) Neural Comput. 2, 1-24.
16. Guo, C. E., Zhu, S. C. & Wu, Y. N. (2003) Int. J. Computer Vision 53, 5-29.