| Statistical modeling of groundwater quality assessment in Iran using a flexible Poisson likelihood M Nadifar, H Baghishani, A Fallah, H Rue arXiv preprint arXiv:1908.02344, 2019 | 5 | 2019 |
| Flexible Bayesian modeling of counts: constructing penalized complexity priors M Nadifar, H Baghishani, T Kneib, A Fallah arXiv preprint arXiv:2105.08686, 2021 | 3 | 2021 |
| Bayesian Regression Model with Finite Mixture Bivariate Poisson Response Variable A Fallah, M Nadifar, R Kazemi Journal of Statistical Sciences 7 (1), 77-102, 2013 | 2 | 2013 |
| A Flexible Generalized Poisson Likelihood for Spatial Counts Constructed by Renewal Theory, Motivated by Groundwater Quality Assessment M Nadifar, H Baghishani, A Fallah Journal of Agricultural, Biological and Environmental Statistics 28 (4), 726-748, 2023 | 1 | 2023 |
| A flexible Bayesian nonconfounding spatial model for analysis of dispersed count data M Nadifar, H Baghishani, A Fallah Biometrical Journal 64 (4), 758-770, 2022 | 1 | 2022 |
| A Bayesian Semi-Parametric Spatial Count Model for Analysing Lung Cancer Mortality M Nadifar, A Bekker, M Arashi on Spatial Statistics and Its Applications, 57, 2023 | | 2023 |
| Analysis of Space-Time Count Data Using the Flexible Gamma-Count Model M Nadifar, H Baghishani, A Fallah Journal of Statistical Sciences 15 (1), 275-301, 2021 | | 2021 |
| A flexible Bayesian non-confounding spatial model for analysis of dispersed count data in clinical studies M Nadifar, H Baghishani, A Fallah arXiv preprint arXiv:2105.09893, 2021 | | 2021 |
Afshin FallahDepartment of Statistics, Imam Khomeini International University, Qazvin, IranVerified email at sci.ikiu.ac.ir
