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Results: 14
Number of items: 14
  • Vogels, L., Mohammadi, R., Schoonhoven, M., & Birbil, Ş. İ. (2024). Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison [Data set]. Taylor & Francis. https://doi.org/10.6084/m9.figshare.26880600.v1
  • Open Access
    Mohammadi, R. (2024). [Review of F. Liang, B. Jia (2023) Sparse graphical modeling for high dimensional data: a paradigm of conditional independence tests]. Journal of the American Statistical Association, 119(547), 2421-2422. https://doi.org/10.1080/01621459.2024.2375035
  • Open Access
    Vogels, L., Mohammadi, R., Schoonhoven, M., & Birbil, S. I. (2024). Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison. Journal of the American Statistical Association, 119(548), 3164-3182. https://doi.org/10.1080/01621459.2024.2395504
  • Open Access
    Huth, K. B. S., de Ron, J., Goudriaan, A. E., Luigjes, J., Mohammadi, R., van Holst, R. J., Wagenmakers, E.-J., & Marsman, M. (2023). Bayesian Analysis of Cross-Sectional Networks: A Tutorial in R and JASP. Advances in Methods and Practices in Psychological Science, 6(4). https://doi.org/10.1177/25152459231193334
  • Open Access
    Saadatmand, S., Salimifard, K., Mohammadi, R., Kuiper, A., Marzban, M., & Farhadi, A. (2023). Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients. Annals of Operations Research, 328, 1043-1071. https://doi.org/10.1007/s10479-022-04984-x
  • Open Access
    Dehdar, S., Salimifard, K., Mohammadi, R., Marzban, M., Saadatmand, S., Fararouei, M., & Dianati-Nasab, M. (2023). Applications of different machine learning approaches in prediction of breast cancer diagnosis delay. Frontiers in Oncology, 13, Article 1103369. https://doi.org/10.3389/fonc.2023.1103369
  • Open Access
    Mohammadi, R., Massam, H., & Letac, G. (2023). Accelerating Bayesian Structure Learning in Sparse Gaussian Graphical Models. Journal of the American Statistical Association, 118(542), 1345-1358 . https://doi.org/10.1080/01621459.2021.1996377
  • Mohammadi, R., Massam, H., & Letac, G. (2021). Accelerating Bayesian Structure Learning in Sparse Gaussian Graphical Models [Data set]. figshare Academic Research System. https://doi.org/10.6084/m9.figshare.17311547.v1
  • Open Access
    Mohammadi, R., & Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models. Journal of Statistical Software, 89(3). https://doi.org/10.18637/jss.v089.i03
  • Dyrba, M., Grothe, M. J., Mohammadi, A., Binder, H., Kirste, T., & Teipel, S. J. (2018). Comparison of Different Hypotheses Regarding the Spread of Alzheimer’s Disease Using Markov Random Fields and Multimodal Imaging. Journal of Alzheimer's Disease, 65(3), 731-746. https://doi.org/10.3233/JAD-161197
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