Tel: 012 420 2523 Email: [email protected] Position: Full Professor  Head of Department of Statistics: 2012- February 2022 Focus Area Coordinator: Statistical Theory and Applied Statistics (see link), Centre of Excellence in Mathematical and Statistical Sciences, University of the Witwatersrand Current NRF Rating: C1 Academic qualifications: BSc, BSc Hons, HDE, MSc (UJ), PhD (UNISA)

Research interests: Bayesian statistics, Computational and Methodological Distribution theory; Directional statistics; Matrix variate / multivariate statistics; modal inference, network learning and graphical models; machine learning

Current postgraduate students:

PhD: C Geldenhuys, M Wagener, J Smith, R M Salgado, A van Wyk, A Otto, D van Wyk

Various masters and honours students currently under my supervision

Previous postgraduate students:

PhD (past 10 years): R Ehlers, K Adamski, J Kleyn, J van Niekerk, MT Loots, JT Ferreira, S Makgai, P Nagar

Various masters and honours students successfully completed

Awards and scientific/scholarly recognition:

• Elected member of the International Statistical Institute (ISI)
• 2001-2006: NRF L rating
• From 2007: NRF C2 rating.
• From 2019: NRF C1 rating
• Received medal S2 A3 from the Southern Africa Association for the Advancement of Science.
• Statistics Publication Impact award 2022- COE_ MASS.
• Exceptional Academic Achiever Award- University of Pretoria, 2023.

Associate Editor:

• Communications in Statistics-Theory and Methods (LSTA)/Simulation and Computation (LSSP).
• Journal of Iranian Statistical Society
• Guest editor for the STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING journal for the Special Issue on Computational Techniques in Theoretical and Applied Statistics, Vol. 6, September 2018.
• Guest editor for MATHEMATICAL PROBLEMS IN ENGINEERING Special Issue on Recent Trends in Statistical Methodologies within Communications and Systems Engineering, October 2019.
• Editor of Springer Book: Computational and Methodological Statistics and Biostatistics – Contemporary Essays in Advancement. Springer Nature. 2020.  ISBN 978-3-030-42195-3
• Editor of Springer Book: Innovations in multivariate statistical modeling: navigating theoretical and multidisciplinary domains. Springer Nature.  ISBN 978-3-031-13970-3

Selected list of publications:

• SMITH, J, ARASHI, M & BEKKER, A (2022). Empowering Differential Networks Using Bayesian Analysis. Plos One. PLoS ONE 17(1): e0261193. https://doi. org/10.1371/journal.pone.0261193
• SALEHI, M, BEKKER, A & ARASHI, M (2022). Clustering via semi-parametric density estimation with skew-symmetric kernels. Journal of Classification; https://doi.org/10.1007/s00357-022-09425-9
• RAD, NN, BEKKER, A & ARASHI, M (2022). Enhancing wind direction prediction of South Africa wind energy hotspots with Bayesian mixture modeling"  Scientific reports, 12:11442 https://doi.org/10.1038/s41598-022-14383-8.
• BEKKER, A, HASHEMI, F & ARASHI, M (2022). Flexible factor model for handling missing data in supervised learning. Communications in Mathematics and Statistics. https://doi.org/10.1007/s40304-021-00260-9.
• FERREIRA, J.T., BOTHA, T. &BEKKER, A. (2022). Tsallis and other generalised entropy forms subject to Dirichlet mixture priors. Symmetry, 2022, 14, 1110. https://doi.org/10.3390/sym14061110.
• BEKKER , A., FERREIRA, J.T., HUMAN, S.W. & ADAMSKI, K. (2022).Capturing a Change in the Covariance Structure of a Multivariate Process, Symmetry, 14(1), 156; https://doi.org/10.3390/sym14010156
• ARASHI, A.  BEKKER, A, SALEHI M, MILLARD S, CRONJE T, & GOLPAYGANI, M (2022). Evaluating prediction of COVID-19 at provincial level of South Africa; a statistical perspective. Environmental Science and Pollution Research. 29, 21289-21302doi: 10.1007/s11356-021-17291-y.
• ARASHI, M , RAD, NN, BEKKER, A  &  LEY, C (2022). A Coming Together of Bayesian Inference and Skew Spherical Data. Frontiers in BIG DATA, doi: 10.3389/fdata.2021.769726.
• HASHEMI, F, BEKKER, A, SMITH, K & ARASHI, M (2022). Sibling rivalry within inverse Weibull family to predict the COVID-19 spread in South Africa. Communications in Statistics-Case studies and Data Analysis, 8(1),119-132. https://doi.org/10.1080/23737484.2021.1979433.
• HUMAN, SW., BEKKER, A. FERREIRA, JT and MIJBURG, PA (2022).  A Bivariate Beta from Gamma Ratios for Determining a Potential Variance Change Point: Inspired from a Process Control Scenario. Mathematical and Computational Applications 27, 61. https://doi.org/10.3390/mca2704006 .
• FERREIRA, JT, BOTHA, C & BEKKER, A. (2022). Wasserstein distance as discriminator within the Dirichlet family. SASA proceedings, 1-14.
• KHEYRI, A., ARASHI, M & BEKKER, A.. (2022). High-dimensional precision matrix estimation through GSOS with application in foreign exchange market. Mathematics, 10, 4232. https://doi.org/10.3390/ math10224232.
• BILANKULU, V, BEKKER, A & MARQUES, FJ (2021). The Ratio of Independent Generalized Gamma Random Variables with Applications. Computational and Mathematical Methods, 3(1) doi.org/10.1002/cmm4.1061.
• SALEH, M, ARASHI, M,  BEKKER, A,  FERREIRA, JT, CHEN, D,  ESMAEIL, F & FRANCES, M (2021).  A synergetic R Shiny portal to track COVID-19 demographic information. Frontiers in Public Health. doi: 10.3389/fpubh.2020.623624
• HASHEMI, F, NADERI, M, JAMALIZADEH, A & BEKKER, A (2021). A flexible factor analysis based on the class of mean mixture of normal distributions. Computational Statistics and Data Analysis,157,107162 https://doi.org/10.1016/j.csda.2020.107162.
• ROOZEGAR, R, BALAKRISHNAN, N, BEKKER, A & JAMALIZADEH, A (2021). On multivariate selection of scale mixtures of normal distributions. Brazilian Journal of Probability and Statistics, 35 (2), 351-374.
• NAGAR, P, BEKKER, A & ARASHI, M (2021). Mean mixtures in directional statistics. Proceedings of 2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.
• VAN NIEKERK, J, BEKKER, A & ARASHI, M (2021). Matrix-variate beta generators - developments and application. -Invited: Special issue of Journal of the Iranian Statistical Society- Behboodian Memorial issue, Volume 20, No. 01, June 2021
• BOTHA, T, FERREIRA, JT & BEKKER, A (2021). Alternative Dirichlet Priors for Estimating Entropy via a Power Sum Functional, Mathematics, 9, 1493. https://doi.org/10.3390/math9131493.
• MAKGAI, SL, BEKKER, A & ARASHI, M (2021). Compositional data modelling through Dirichlet innovations Mathematics, 9, 2477. https://doi.org/10.3390/math9192477 
• RAD,NN,  BEKKER, A &  ARASHI, M (2021). Bayesian inference for skew-wrapped Cauchy mixture model using a modified Gibbs sampler. Proceedings of 2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.
• ARASHI, M, RAD, NN, BEKKER, A & SCHUBERT, WD (2021). Möbius transformation-induced distributions provide better modelling for protein architecture. Mathematics, 9, (21), 2749; https://doi.org/10.3390/math9212749
• FERREIRA, J.T., BEKKER, A., BOTHA, C. & MAKGAI, S. (2021). A note on the probabilistic determinant of independent generalized beta entries. Annual Proceedings of the South African Statistical Association Conference, SASA 2021.
• FERREIRA, J, BEKKER, A & ARASHI, M (2020). Advances in Wishart-type modelling of channel capacity. RevStat-Statistical Journal, 18 (3) 237 -255
• NADERI, M, BEKKER, A, ARASHI, M & JAMALIZADEH, A (2020). A theoretical framework for Landsat data modeling based on the matrix variate mean-mixture of normal model. PLoS One, 15(4): e0230773. 2https://doi.org/10.1371/journal.pone.0230773
• NADERI, M, HASHEMI, F, BEKKER, A & JAMALIZADEH, A (2020). Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum–Saunders mixture model. Applied Mathematics and Computation, 376: 125109
• ARASHI, M, NAGAR, P & BEKKER, A (2020). Joint probabilistic modelling of wind speed and wind direction for wind energy analysis: a case study in Humansdorp and Noupoort. Sustainability, 12 (11), 4371; https://doi.org/10.3390/su12114371
• RAD, NN, BEKKER, A & ARASHI, M (2020). A Unified Model for Skew Circular Data.  Proceedings FUSION 2020.
• NEETHLING, A, FERREIRA, JT, BEKKER A & NADERI, M (2020). Skew generalised normal innovations for the AR(p) model.  Symmetry,12, 1253; doi:10.3390/sym12081253
• VAN NIEKERK, J, BEKKER, A & ARASHI, M (2019). Beta regression in the Presence of Outliers- A wieldy Bayesian solution. Statistical Methods in Medical Research,28(12), 3729-3740DOI: 10.1177/0962280218814574
• ARASHI, M, BEKKER, A & VAN NIEKERK, J (2019). Weighted Distributions of Eigenvalues. Linear Algebra and its Applications, 561, 1-17.
• BEKKER, A, ARASHI, M, & FERREIRA, JT (2019). New bivariate gamma types with MIMO application. Communications in Statistics-Theory and Methods, 48,3, 596-615.
• MARQUES, F, LOOTS, MT & BEKKER, A (2019). Series representations for density functions of a family of distributions - application to the sum of independent Rayleigh random variables. Math Meth Appl Sci., 1–18.
• FERREIRA, JT & BEKKER, A (2019). A unified complex noncentral Wishart type distribution inspired by massive MIMO systems. Journal of Statistical Distributions and Applications, 6(4),1-19.
• BEKKER, A, NAGAR, P, ARASHI, M & RAUTENBACH, H (2019). From Symmetry to Asymmetry on the Disc Manifold: Modelling of Marion Island Data. Symmetry, 11 (8) p1030-1030. DOI: 10.3390/sym11081030.
• BEKKER, A & FERREIRA, JT (2018). Bivariate gamma type distributions for modeling wireless performance metrics. Statistics, Optimization and Information Computing, 6, 335–353.
• BEKKER, A, FERREIRA, JT, ARASHI, A &. ROWLAND, B (2018). Computational methods applied to a skewed generalised normal family. Communications in Statistics - Simulation and Computation. https://doi.org/10.1080/03610918.2018.1530785.
• VAN NIEKERK, J, BEKKER, A & ARASHI, M (2017). A gamma-mixture class of distributions with Bayesian application. Communications in Statistics- Simulation and Computation, (46) 10, 8152-8165, http://dx.doi.org/10.1080/03610918.2016.1267754
• BEKKER, A, VAN NIEKERK, J & ARASHI, M (2017). Wishart distributions: Advances in theory with Bayesian application. Journal of Multivariate Analysis, 155,  272–283  http://dx.doi.org/10.1016/j.jmva.2016.12.002
• KLEYN, J, ARASHI, M, BEKKER, A & MILLARD, S (2017). Preliminary Testing of the Cobb-Douglas Production Function and Related Inferential Issues. Communications in Statistics- Simulation and Computation, 46(1) 469-488. http://dx.doi.org/10.1080/03610918.2014.968724.
• ARASHI, M, BEKKER, A & VAN NIEKERK, J (2017). The weighted-type Wishart distributions with application. RevStat-Statistical Journal, 15(1), 205-222.
• FERREIRA, J ,BEKKER, A & ARASHI, M (2016). Objective Bayesian estimators for the right censored Rayleigh distribution: evaluating the Al-Bayatti loss function. RevStat-Statistical Journal, 14(4) 433-454.
• JACOBS, R, BEKKER, A, VAN DER VOET, H & TER BRAAK, C (2015). Parametric estimation of P(X > Y) for normal distributions in the context of probabilistic environmental risk assessment. PeerJ 3:e1164; DOI 10.7717/peerj.1164.
• ARASHI, M, BEKKER, A, ROUX, JJJ & RATNAPARKHI, M (2014). A New Definition of Form-Invariance Matrix Variate Distributions. South African Statist. J., 48, 205 – 212.
• ADAMSKI, K, HUMAN, SW, BEKKER, A & ROUX, JJJ (2013). Noncentral generalized multivariate beta type II distribution. RevStat-Statistical Journal, 11, 1, 17-43.
• LOOTS, MT, BEKKER, A, ARASHI, M & ROUX, JJJ (2013). On the real representation of quaternion variables. Statistics, 47(6), 1224-1240.
• ADAMKSI, K, HUMAN, SH & BEKKER, A (2012). A generalized multivariate beta distribution: control charting when the measurements are from an exponential distribution. Statistical Papers, Volume 53, Issue 4, 1045-1064. 
• BEKKER, A, ROUX, JJJ, EHLERS, R & ARASHI, M (2012). Distribution of the product of determinants of noncentral bimatrix beta variates. Journal of Multivariate Analysis, 109, 73-87. http://dx.doi.org/10.1016/j.jmva.2012.02.016
• BEKKER, A  ROUX, JJJ & ARASHI, M (2011). Exact nonnull distribution of Wilks’s Statistic: ratio and product of independent components.  Journal of Multivariate Analysis, 102, 619-628. (http://dx.doi.org/10.1016/j.jmva.2010.11.005)
• BEKKER, A, ROUX, JJJ & ARASHI, M (2011). Wishart ratios with dependent structure: new members of the bimatrix beta type IV. Linear Algebra and its Applications, 435, 3243–3260.