메뉴 건너뛰기




Volumn 42, Issue 1-2, 2006, Pages 69-83

Learning parameters of Bayesian networks from incomplete data via importance sampling

Author keywords

Bayesian networks; Bayesian statistics; Incomplete data; MCMC; Parameter learning

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; DATA REDUCTION; LEARNING SYSTEMS; STATISTICAL METHODS;

EID: 33645980673     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2005.10.005     Document Type: Article
Times cited : (34)

References (19)
  • 2
    • 33745454493 scopus 로고    scopus 로고
    • C. Riggelsen, A. Feelders, Learning Bayesian network models from incomplete data using importance sampling, in: R.G. Cowell, Z. Ghahramani (Eds.), Proc. of Artificial Intelligence and Statistics, 2005, pp. 301-308.
  • 4
  • 5
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by data augmentation
    • Tanner M., and Wong W. The calculation of posterior distributions by data augmentation. Journal of the American Statistical Association 82 398 (1987) 528-540
    • (1987) Journal of the American Statistical Association , vol.82 , Issue.398 , pp. 528-540
    • Tanner, M.1    Wong, W.2
  • 6
    • 58149210716 scopus 로고
    • The EM algorithm for graphical association models with missing data
    • Lauritzen S.L. The EM algorithm for graphical association models with missing data. Computational Statistics and Data Analysis 19 (1995) 191-201
    • (1995) Computational Statistics and Data Analysis , vol.19 , pp. 191-201
    • Lauritzen, S.L.1
  • 8
    • 33645967120 scopus 로고    scopus 로고
    • M. Ramoni, P. Sebastiani, Learning Bayesian networks from incomplete databases, in: D. Geiger, P. Shenoy (Eds.), Proc. of the Conf. on Uncertainty in AI, 1997, pp. 401-408.
  • 9
    • 0012483452 scopus 로고
    • A comparison of sequential learning methods for incomplete data
    • Cowell R.G., Dawid A.P., and Sebastiani P. A comparison of sequential learning methods for incomplete data. Bayesian Statistics 5 (1995) 533-541
    • (1995) Bayesian Statistics , vol.5 , pp. 533-541
    • Cowell, R.G.1    Dawid, A.P.2    Sebastiani, P.3
  • 10
    • 84986980101 scopus 로고
    • Sequential updating of conditional probabilities on directed graphical structures
    • Spiegelhalter D.J., and Lauritzen S.L. Sequential updating of conditional probabilities on directed graphical structures. Networks 20 (1990) 579-605
    • (1990) Networks , vol.20 , pp. 579-605
    • Spiegelhalter, D.J.1    Lauritzen, S.L.2
  • 11
    • 34249832377 scopus 로고
    • A Bayesian method for the induction of probabilistic networks from data
    • Cooper G., and Herskovits E. A Bayesian method for the induction of probabilistic networks from data. Machine Learning 9 4 (1992) 309-347
    • (1992) Machine Learning , vol.9 , Issue.4 , pp. 309-347
    • Cooper, G.1    Herskovits, E.2
  • 12
    • 34249761849 scopus 로고
    • Learning Bayesian networks: the combination of knowledge and statistical data
    • Heckerman D., Geiger D., and Chickering D. Learning Bayesian networks: the combination of knowledge and statistical data. Machine Learning 20 (1995) 197-243
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.3
  • 13
    • 0001667705 scopus 로고
    • Bayesian inference in econometric models using Monte Carlo integration
    • Geweke J. Bayesian inference in econometric models using Monte Carlo integration. Econometrica 74 6 (1989) 1317-1339
    • (1989) Econometrica , vol.74 , Issue.6 , pp. 1317-1339
    • Geweke, J.1
  • 14
    • 78649424388 scopus 로고
    • Weighted average importance sampling and defensive mixture distributions
    • Hesterberg T. Weighted average importance sampling and defensive mixture distributions. Technometrics 37 2 (1995) 185-194
    • (1995) Technometrics , vol.37 , Issue.2 , pp. 185-194
    • Hesterberg, T.1
  • 16
    • 0000130823 scopus 로고
    • A fast procedure for model search in multidimensional contingency tables
    • Edwards D., and Havránek T. A fast procedure for model search in multidimensional contingency tables. Biometrika 72 2 (1985) 339-351
    • (1985) Biometrika , vol.72 , Issue.2 , pp. 339-351
    • Edwards, D.1    Havránek, T.2
  • 19
    • 0006407254 scopus 로고    scopus 로고
    • WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility
    • Lunn D.J., Thomas A., Best N., and Spiegelhalter D. WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 10 4 (2000) 325-337
    • (2000) Statistics and Computing , vol.10 , Issue.4 , pp. 325-337
    • Lunn, D.J.1    Thomas, A.2    Best, N.3    Spiegelhalter, D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.