Research Interests

Interdisciplinary subjects are integral to a wide spectrum of projects in various fields in real-world applications where Statistics and data science are the fields that are used to extract actionable knowledge insights from data and solve problems in these projects. My research interest lies broadly in the development of statistical models and machine learning algorithms for the analysis of time series, econometrics, and Spatio-temporal data mining.

Colorful software or web code on a computer monitor

Selected Publications

Rodríguez M., Leiva V., Martin-Barreiro, C., Cabezas X., Mahdi, E. (2023). The r-hypergeometric distribution: Characterization, simulations, and applications. Mathematical Methods in Applied Sciences; 46(5): 5208-5233.

Mahdi, E. & Fisher J. Thomas (2022). Bootstrapping a powerful mixed portmanteau test for time series, Journal of Applied Statistics, https://doi.org/10.1080/02664763.2022.2121384.
Mahdi E, Al-Abdulla A. Impact of COVID-19 Pandemic News on the Cryptocurrency Market and Gold Returns: A Quantile-on-Quantile Regression Analysis. Econometrics. 2022; 10(2):26. https://doi.org/10.3390/econometrics10020026.
Mahdi, E., Leiva, V., Mara’Beh, S., Martin-Barreiro, C. A New Approach to Predicting Cryptocurrency Returns Based on the Gold Prices with Support Vector Machines during the COVID-19 Pandemic Using Sensor-Related Data. Sensors 2021, 21, 6319. https://doi.org/10.3390/s21186319.
Mahdi, E. (2021). New Goodness-of-Fit Tests for Time Series Models. arXiv: 2008.08176. https://arxiv.org/abs/2008.08176.
Mahdi, E., Alshamari S., Khashabi, M., Alkorbi, A. (2021). Hierarchical Bayesian Spatio-Temporal Modeling for PM10 Prediction. Journal of Applied Mathematics. https://doi.org/10.1155/2021/8003952.
Mahdi, E. Atta, A. M. A., Abuzaid, A. H., (2020). Empirical variogram for achieving the best valid variogram. Communications for Statistical Applications and Methods, 27(5), 547-568. https://doi.org/10.29220/CSAM.2020.27.5.547.
Abuzaid, A. H., Abed, E., Atta, A. M. A., Mahdi, E. (2020). An Alternative Diagnostic Procedure for Meta-Regression. Statistics, Optimization & Information Computing, 8(1), 54-65. https://doi.org/10.19139/soic-2310-5070-864.
Atta, A., Shoraim, M., Yahya, S., Abuzaid, A. H., Mahdi, E. (2020). Enhancing R Control Chart Performance in Monitoring Process Dispersion using Scaled Weighted Variance Method for Skewed Populations. Journal of Engineering and Applied Sciences (JEAS), 15(6), 1508 -1514. 10.36478/jeasci.2020.1508.1514.
Mahdi E., (2020). portes: An R Package for Portmanteau Tests in Time Series Models. arXiv: 2005.00931.https://arxiv.org/abs/2005.00931.
Mahdi, E., Provost, S. B., Salha, R. B., Nashwan, I. I.H. (2017). Multivariate time series modeling of monthly rainfall amounts. Electronic Journal of Applied Statistical Analysis, 10(1), 65-81. 10.1285/i20705948v10n1p65.
Mahdi E. (2017). Kernel-based portmanteau diagnostic test for ARMA time series models. Cogent Mathematics (Statistics), 4(1), 1296327. https://doi.org/10.1080/23311835.2017.1296327.
Mahdi E. (2016). Portmanteau test statistics for seasonal serial correlation in time series models. SpringerPlus, volume 5: 1485. Springer Nature. http://springerplus.springeropen.com/articles/10.1186/s40064-016-3167-4.
Mahdi E., McLeod A.I. (2012). Improved Multivariate Portmanteau Test. Journal of Time Series Analysis, 33(2), pages 211–222. http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2011.00752.x/abstract.
McLeod, A. I., Yu H., Mahdi E. (2012). Time Series Analysis with R. In Time Series Analysis: Methods and Applications, Chapter 23 (pp. 661-712) in Handbook in Statistics, Volume 30. Elsevier. http://www.sciencedirect.com/science/handbooks/01697161.