The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines
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Citations
Cites
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Doob, J. L., & Doob, J. L. (1953) · CERN Document Server (European Organization for Nuclear Research) · Cited by 9,053
Nelsen, R. B. (1999) · Lecture Notes in Statistics · doi:10.1007/978-1-4757-3076-0 · Cited by 7,744
Information theory and statistics
(1959) · Journal of the Franklin Institute · doi:10.1016/0016-0032(59)90368-0 · Cited by 7,094
Introduction to Bayesian Networks
(2019) · Operational Risk Modelling in Financial Services · doi:10.1002/9781119508557.ch12 · Cited by 2,569
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference
Strawderman, R. L., & Gamerman, D. (2000) · Journal of the American Statistical Association · doi:10.2307/2669581 · Cited by 1,909
A distribution-free approach to inducing rank correlation among input variables
Iman, R. L., & Conover, W. J. (1982) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918208812265 · Cited by 1,620
Vines--a new graphical model for dependent random variables
Bedford, T., & Cooke, R. M. (2002) · The Annals of Statistics · doi:10.1214/aos/1031689016 · Cited by 1,418
Self-citationJoe, H. (1996) · Institute of Mathematical Statistics Lecture Notes - Monograph Series · doi:10.1214/lnms/1215452614 · Cited by 778
Minimally informative distributions with given rank correlation for use in uncertainty analysis
Meeuwissen, A. M. H., & Bedford, T. (1997) · Journal of Statistical Computation and Simulation · doi:10.1080/00949659708811806 · Cited by 66
Self-citation
Cited by
Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine
Brechmann, E. C., & Schepsmeier, U. (2013) · Journal of Statistical Software · doi:10.18637/jss.v052.i03 · Cited by 498
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., & Vrac, M. (2017) · Hydrology and Earth System Sciences · doi:10.5194/hess-21-2701-2017 · Cited by 373
Gräler, B., van den Berg, M. J., Vandenberghe, S., Petroselli, A., Grimaldi, S., De Baets, B., & Verhoest, N. E. C. (2013) · Hydrology and Earth System Sciences · doi:10.5194/hess-17-1281-2013 · Cited by 313
Pair copula constructions for multivariate discrete data
Panagiotelis, A., Czado, C., & Joe, H. (2012) · Journal of the American Statistical Association · doi:10.1080/01621459.2012.682850 · Cited by 194
Derivatives and Fisher information of bivariate copulas
Schepsmeier, U., & Stöber, J. (2014) · Statistical Papers · doi:10.1007/s00362-013-0498-x · Cited by 66
Metadata
- Authors
- Bedford, T., & Cooke, R. M.
- Venue
- Annals of Mathematics and Artificial Intelligence
- Published
- 2001-08
- Volume
- 32
- Issue
- 1-4
- Pages
- 245-268
- ISSN
- 1012-2443 (ISSN-L)
- 1573-7470
- OpenAlex
- W1590831612
- Cited by
- 937
- References
- 10
- FWCI
- 0.38
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bedford, T., & Cooke, R. M. (2001). Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines. Annals of Mathematics and Artificial Intelligence. https://doi.org/10.1023/a%3A1016725902970
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
