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Mahsa Nadifar

A Flexible Generalized Poisson Likelihood for Spatial Counts Constructed by Renewal Theory, Motivated by Groundwater Quality Assessment
2023 · Mahsa Nadifar, Hossein Baghishani, et al. · Journal of Agricultural Biological and Environmental Statistics · 4
A flexible Bayesian nonconfounding spatial model for analysis of dispersed count data
2022 · Mahsa Nadifar, Hossein Baghishani, et al. · Biometrical Journal · 2
Flexible Bayesian Modeling of Counts: Constructing Penalized Complexity Priors
2021 · Nadifar, Mahsa, Baghishani, Hossein, et al. · arXiv (Cornell University) · 2
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Statistical modeling of groundwater quality assessment in Iran using a flexible Poisson likelihood
2019 · Nadifar, Mahsa, Baghishani, Hossein, et al. · arXiv (Cornell University) · 2
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Bayesian semi-parametric spatial modeling of dispersed count data with INLA: applications in public health and climate risk
2026 · Mahsa Nadifar, Andriette Bekker, et al. · Stochastic Environmental Research and Risk Assessment · 1
A Nonstationary Spatial Count Regression Using Gamma-Count: A Case Study on Canadian Precipitation
2026 · Mahsa Nadifar, Andriëtte Bekker, et al. · Chapman & Hall/CRC eBooks
Flexible Bayesian modeling of non-equidispersed counts with penalized complexity priors in disease incidence studies
2026 · Mahsa Nadifar, Hossein Baghishani, et al. · Statistical Methods in Medical Research
SpatGC: Bayesian Modeling of Spatial Count Data
2024 · Mahsa Nadifar, Hossein Baghishani
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A flexible Bayesian non-confounding spatial model for analysis of dispersed count data in clinical studies
2021 · Nadifar, Mahsa, Baghishani, Hossein, et al. · arXiv (Cornell University)
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Analysis of Space-Time Count Data Using the Flexible Gamma-Count Model
2021 · Mahsa Nadifar, Hossein Baghishani, et al. · Journal of Statistical Sciences
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Works count: 11
Citation count: 11
H-index: 2
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