• 2026 

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• Sadeghkhani, A, Beyond Skellam: Beta--Gamma Compounded Skellam Regression for Differences of Counts, AStA Advances in Statistical Analysis. 2026.

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• Sadeghkhani, A, Covariate-Dependent Kato–Jones Mixtures with an Explicit Uniform Background for Wind-Direction Regimes, Statistical Methods & Applications, 2026.

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• Sadeghkhani, A, Hidden Markov Modeling of Hockey Shot Angles with a Uniform Transient State, Japanese Journal of Statistics and Data Science, 2026.

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• Sadeghkhani, A, Grouped-Poisson Hurdle Regression for Underdispersed Ecological Counts. Journal of Applied Statistics, 2026.

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• Sadeghkhani, A, Prediction-Guided Hierarchical Clustering for Population-Level Regression. International Journal of Data Science, 2026.

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• Sadeghkhani, A. Sadeghkhani, A. Exact one‑sided inference for random‑effects quantile in negative binomial regression for ecological count data. Environmental and Ecological Statistics. 2026.

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• Sadeghkhani, A. Wasserstein Regression, Forecasting, and Change-Point Detection for Daily Traffic Flow Distributions. Statistical Analysis and Data Mining​. 2026.

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• Sadeghkhani, A. Bayesian Tail Index Learning for Poisson-Tweedie Counts via a Poisson-GIG Bridge. Journal of Agricultural, Biological, and Environmental Statistics. 2026.

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• Samaneh Nazari, Mohammad Arashi, and Sadeghkhani, A. Bayesian Structure Learning of Directed Acyclic Graphs for Identifying Causal Effects of Weather Elements in South Africa. In A. Bekker, P. Nagar, J. Ferreira, B. Erasmus, and A. Ramoelo (Eds.), Environmental Modelling with Contemporary Statistics: Learning, Directionality, and Space-Time Dynamics. Chapman and Hall/CRC, forthcoming, 2026. (Book Chapter)

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•  Sadeghkhani, A. Inner-Envelope Matrix Autoregression. Journal of Multivariate Analysis. 2026. 

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• Sadeghkhani, A. Fast Bayesian Model Selection for Tail-Regime Poisson Mixtures. Communications in Statistics - Simulation and Computation.  2026.

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• Sadeghkhani, A. Bayesian Poisson-Lognormal Regression with Compositional Effect Shares for Multivariate Count Data.  Environmetrics.  2026.

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• Sadeghkhani, A., Modeling Interval-Valued Data in the Presence of Additional Information. Annals of Data Science, 2026.​

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• Sadeghkhani, A. Robust Analysis of Multivariate Count Data under Stopped--Sampling Designs: The Contaminated Dirichlet-Negative Multinomial. Journal of Applied Statistics. 2026.​​

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• Sadeghkhani, A., Sadeghkhani, A.,  Hussein, A. Inference for Multivariate Interval Data: Bridging Frequentist and Bayesian Paradigms. Colombiana de Estadística, 2026.

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• 2025

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• Sadeghkhani, A. Constrained Bayesian Estimation and Predictive Modeling for Multivariate Count Data in Ecology. Environmental and Ecological Statistics, 2025.

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• Platjouw, E., Sadeghkhani, A., Manisera, M., Zuccolotto, P., & Ley, C. A New Approach to Basketball Game Predictions by Simulating Games Based on the Predicted Numbers and Types of Plays. In Statistical Methods and Applications in Systems Assurance and Quality, CRC Press, 2025.

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• Sadeghkhani, A., Sadeghkhani, A. On Inference of Boxplot Symbolic Data: Applications in Climatology. Advances in Statistical Climatology, Meteorology and Oceanography, 2025.

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• Sadeghkhani, A. Closed-Form Predictive Density Estimation for Bivariate Gamma Distribution. Revista Colombiana de Estadística, 2025.

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• Sadeghkhani, A. On Multivariate Triangular-valued data. Discover Data, 2025.

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• 2024

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• Nazari, S., Arashi, M., Sadeghkhani, A. Weighted Inverse Gamma Innovation for the Structure Learning of DAGs. Japanese Journal of Statistics and Data Science, 2024.

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• Sadeghkhani, A., Sadeghkhani, A. Interval-Valued Random Matrices. Entropy, 2024.

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• Sadeghkhani, A. Closed-Form Bayesian Estimation and Prediction in a New Bivariate Rayleigh Model Using Jeffreys’ Prior. Journal of Applied Probability and Statistics, 2024.

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• 2023–2017 

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• Sadeghkhani, A., Arashi, M. On Matrix Variate Density Estimation Problem. Journal of the Korean Statistical Society, 2023.

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• Sadeghkhani, A. On Improving the Posterior Predictive Distribution of the Difference Between Two Independent Poisson Distributions. Sankhya B, 2022.

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• Sadeghkhani, A. K₁K₂-Inflated Conway–Maxwell–Poisson Model Bayesian Predictive Modeling with an Application in Soccer Matches. American Journal of Mathematical and Management Sciences, 2021.

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• Sadeghkhani, A. Predicting the Scoring Time in Hockey. Journal of Statistical Theory and Practice, 2021.

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• Sadeghkhani, A., Ahmed, S. E. Predictive Density Estimation of K-Inflated Poisson Models with and without Additional Information. Revista Colombiana de Estadística, 2020.

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• Sadeghkhani, A., Ahmed, S. E. Predictive Distribution Estimation in Multiple-Inflated Poisson Models Applied to Ice Hockey Data. Model Assisted Statistics and Applications, 2020.

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• Sadeghkhani, A., Ahmed, S. E. A Bayesian Approach to Predict the Number of Goals in Hockey. Stats, 2019.

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• Sadeghkhani, A., Ahmed, S. E., et al. Bayesian Predictive Densities as an Interpretation of a Class of Skew-Student t Distributions with Application to Medical Data. In ICMSEM 2019, Springer.

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• Sadeghkhani, A., Peng, Y., Lin, D. A Parametric Bayesian Approach in Density Ratio Estimation. Stats, 2019.

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• Marchand, É., Sadeghkhani, A.. Predictive Density Estimation with Additional Information. Electronic Journal of Statistics, 2018.

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• Sadeghkhani, A., Ghosh, I. A New Generalized Balakrishnan-Type Skewed-Normal Distribution: Properties and Inference. Communications in Statistics-Theory and Methods, 2017.

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