Publications

(2025). COVID-19 Vaccination and Cardiovascular Events: A Systematic Review and Bayesian Multivariate Meta-Analysis of Preventive Benefits and Risks. International Journal of Preventive Medicine.

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(2025). Testing the hypothesis of a nested block covariance matrix structure with applications to medicine and natural sciences. Mathematical Methods in the Applied Sciences.

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(2025). PSInference: A Package for Synthetic Data.

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(2025). Marginalized LASSO in the low-dimensional difference-based partially linear model for variable selection. Journal of Applied Statistics.

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(2024). TestIndVars: Neutrosophic distributions.

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(2024). PSinference: Inference for Released Plug-in Sampling Single Synthetic Dataset.

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(2024). ntsDatasets: Neutrosophic Data Sets.

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(2024). Comparing Estimation Methods for the PowerPareto Distribution. Econometrics.

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(2024). CBPE: Correlation-Based Penalized Estimators.

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(2023). Testing the independence of variables for specific covariance structures: a simulation study. Mathematical Methods in the Applied Sciences.

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(2023). Regularized Generalized Linear Models to Disclose Host-Microbiome Associations in Colorectal Cancer. 6th International Conference on Mathematics and Statistics.

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(2023). Predicting COVID-19 Hospital Stays with Kolmogorov--Gabor Polynomials: Charting the Future of Care. Information.

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(2023). ntsDists: Neutrosophic Distributions.

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(2023). Neutrosophic Generalized Rayleigh Distribution with Application. Neutrosophic Sets and Systems.

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(2023). Neutrosophic Generalized Exponential Distribution with Application. Neutrosophic Sets and Systems.

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(2023). Feasible Stein-Type and Preliminary Test Estimations in the System Regression. Statistics, Optimization and Information Computing.

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(2023). Combining Kibria-Lukman and Principal Component Estimators for the Distributed Lag Models. Behaviormetrika.

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(2022). Robust estimation through the preliminary test based on the LAD-LASSO. Innovations in Multivariate Statistical Modeling - Navigating Theoretical and Multidisciplinary Domains.

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(2022). Rank-Based Methods for Shrinkage and Selection With Application to Machine Learning. John Wiley and Sons.

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(2022). Differenced-based double shrinking in partial linear models. Journal of Computational Statistics and Modeling.

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(2022). A note on the restricted Enet estimators. Linear Statistical Inference (LinStat).

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(2021). Penalized estimators in Cox regression model. Andishe_ye_Amari.

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(2021). A high-dimensional counterpart for the ridge estimator in multicollinear situations. Mathematics.

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(2020). Dimension Reduction and Shrinkage Estimation in Seemingly Unrelated Regression Models. 15th Iranian Statistical Conference.

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(2019). Preliminary test and Stein-type shrinkage ridge estimators in robust regression. Statistical Papers.

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(2019). Least trimmed ridge estimator under stochastic linear restriction. The 12th Seminar on Probability and Stochastic Process.

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(2019). LAD, LASSO, and related strategies in regression models. Proceedings of the Thirteenth International Conference on Management Science and Engineering Management.

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(2019). A note on preliminary test estimator in high dimensional regression model. Biostatistics and Biometrics.

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(2018). Shrinkage and penalized estimators in weighted least absolute deviations regression models. Journal of Statistical Computation and Simulation.

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(2018). Rank-based Liu regression. Computational Statistics.

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(2018). Rank theory approach to ridge, LASSO, preliminary test and Stein-type estimators: a comparative study. Canadian Journal of Statistics.

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(2018). Preliminary test and Stein-type shrinkage LASSO- based estimators. SORT-Statistics and Operation Research Transactions.

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(2018). On shrinkage estimation: non-orthogonal case. Statistics, Optimization and Information Computing.

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(2017). On shrinkage and selection of treatments ANOVA model. Journal of Statistical Research.

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(2017). Improved robust ridge M-estimation. Journal of Statistical Computation and Simulation.

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(2017). Asymptotic properties of shrinkage LAD estimators. 11th Seminar on Probability and Stochastic Processes.

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(2016). Studying the performance of shrinkage estimators in penalized multiple models with L1 norm. Journal of Statistical Sciences.

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(2016). Steinian shrinkage estimation in high dimensional regression. 13th Iranian Statistical Inference.

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(2016). From Lad-LASSO to PR-LAD estimator. 1st Seminar on Nonparametric Statistics and its Application.

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(2015). Some asymptotic results on improved LASSO estimators. 10th Seminar on Probability and Stochastic Process.

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(2015). Singular ridge regression with stochastic constraints. Communication in Statistics Theory and Methods.

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(2015). Shrinkage estimation through convex optimization. 8th International Conference of the Iranian Society of Operations Research.

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(2015). Improved ridge M-estimators. 46th Annual Iranian Mathematics Conference.

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(2014). Preliminary test approach in high dimensional multivariate regression models. 12th Iranian Statistical Conference.

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(2014). Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model. Journal of Multivariate Analysis.

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(2014). Bayesian analysis in multivariate regression models with conjugate priors. Statistics.

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(2012). On the quadratic loss estimation. The 43rd Annual Iranian Mathematics Conference.

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(2012). Estimating Loss Function Using Shrinkage Stein-Type Estimators. The 11th Iranian Statistical Conference.

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(2012). A note on loss estimation. Applied Mathematics Letters.

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(2011). Estimation loss function in multivariate normal distribution. 6th Iranian Statistics Congress.

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