السيرة الذاتية
Rahim Alhamzawi
Professor of Statistics
Statistics Department
College of Administration and Economics
University of Al-Qadisiyah
Al Dewania
Iraq
Phone: 009647809974280
Fax:
Office: Computer Center
Email: rahim.alhamzawi@qu.edu.iq
Homepage: here
Find me on: ORCID, Google Scholar, ResearchGate,
Mendeley.
Education
PhD Mathematics, Brunel University, UK, 2013.
MSc Statistics, Baghdad University, Iraq, 1999.
BSc Statistics, Al-Qadisiyah University, Iraq, 1992.
Experience
Assistant Lecturer, Al-Qadisiyah University, Department of Statistics, June 2000–October 2003.
Lecturer, Al-Qadisiyah University, Department of Statistics, October 2003– October 2006.
Course in Mathematical statistics, Université de Grenoble (France), 2006.
Assistant Professor, Al-Qadisiyah University, October 2006– September 2016.
Teaching Assistant (GTA), Brunel University, October 2010– June 2013.
Received Graduate Teaching Academy (GTA) Fellow Certification in 2013 from Brunel University.
Professor, Al-Qadisiyah University, 1 September 2016.
Fields of Research Interest
Quantile regression and distributions, Model Selection, Bayesian inference, R Statistical packages.
Biography
I am a Professor of Statistics in the Department of Statistics at University of Al-Qadisiyah. My current
methodological research interests focus on Bayesian variable selection in quantile regression models. I
am also interested in cosmology and gravitational lensing. Specifically, I am interested in understanding how small fluctuations in the early universe grew to form the large-scale structure observed today.
(see , Gravitational lensing by f(R,T) gravity).
Rahim Alhamzawi 2
Awards and Honors
1. Iraqi Science Day (First Place): Ministry of higher education and scientific research prize for best
academic staff member who published papers in international scientific journals. (September, 2021)
2. Medal of Science in Iraqi Science Day - First Place (September, 2018)
3. Iraqi Science Day (First Place): Ministry of higher education and scientific research prize for best
academic staff member who published papers in international scientific journals. (September, 2017)
4. Iraqi Science Day: Ministry of higher education and scientific research prize for best postgraduate
student who published a paper from his research project in international scientific journals sober
(May, 2014)
5. Brunel Vice-Chancellor’s Prize for Doctoral Research (July 2013)
Grants
1. National Institute of Health Research: £68883, 2014–2015, PI with Joanne Lord and Keming Yu.
Project: Bayesain quantile regression analysis of BMI. (2014-2015)
Publications
H-index 14 with Publications 2010 onwards
1. Zainab Alsaadi and Rahim Alhamzawi (2022). Bayesian bridge and reciprocal bridge composite
quantile regression
2. Rahim Alhamzawi and Himel mallick, Erina Paul, Vladimir Svetnik (2021). The reciprocal Bayesian
LASSO Regression. Statistics in Medicine. 40(22), pp. 4830-4849.
3. Esmaeel Ali Alselmawi and Rahim Alhamzawi (2021). Inference with gamma and inverse gamma
prior densities in left-censored regression . Periodicals of Engineering and Natural Sciences. 71–79.
4. Rahim Alhamzawi and Himel mallick (2021). The reciprocal Bayesian bridge for left-censored data .
Communications in Statistics - Simulation and Computation. 1-17.
5. Rahim Alhamzawi (2020). Brq: An R package for Bayesian Quantile Regression. Metron. Accepted.
6. Rahim Alhamzawi and Himel mallick (2020). Bayesian Reciprocal LASSO Quantile Regression.
Communications in Statistics - Simulation and Computation. 1-17.
7. Rahim Alhamzawi (2020). Bayesian single-index quantile regression for ordinal data. Communications in Statistics - Simulation and Computation. 49(5), 1306–1320
8. Rahim Alhamzawi (2019). Bayesian Adaptive Bridge Regression for Ordinal Models with an Application. Iraqi Journal of Science, 170-178.
9. Rahim Alhamzawi (2019). A New Bayesian Group Bridge to Solve the Tobit Model. Iraqi Journal of
Science, 215-222.
10. Rahim Alhamzawi (2019). Bayesian group Lasso regression for left-censored data. Periodicals of
Engineering and Natural Sciences 8 (2), 562-571.
Rahim Alhamzawi 3
11. Rahim Alhamzawi (2019). Quantile Regression and Beyond in Statistical Analysis of Data. Journal
of Probability and Statistics. 2019, 1.
12. Rahim Alhamzawi (2019). New Gibbs sampling methods for Bayesian Regularized Quantile Regression. Computers in Biology and Medicine. 110, 52 – 65.
13. Rahim Alhamzawi (2019).The Bayesian elastic net regression. Communications in Statistics - Simulation and Computation, 47:4, 1168-1178.
14. Hilali, H. K. and Alhamzawi, R. (2019). Bayesian Adaptive Lasso binary regression with ridge
parameter. In Journal of Physics: Conference Series (Vol. 1294, No. 3, p. 032036). IOP Publishing.
15. Aljabri, D. H., Alhamzawi, R. (2019). Bayesian bridge regression for ordinal models with a practical
application. In Journal of Physics: Conference Series (Vol. 1294, No. 3, p. 032030). IOP Publishing.
16. Alhamawi, A., and Alhamawi, R. (2019, September). Generalized Gibbons-Hawking-York term for f
(R) gravity. In Journal of Physics: Conference Series (Vol. 1294, No. 3, p. 032032). IOP Publishing.
17. Rahim Alhamzawi (2018).The Bayesian elastic net regression . Communications in Statistics - Simulation and Computation. 47(4), 1168–1178.
18. Rahim Alhamzawi (2018). A new Gibbs sampler for Bayesian lasso. Communications in Statistics -
Simulation and Computation. 1-17.
19. Alhamzawi, R. and Algamal, Z and Haithem T.M Ali (2018). The Bayesian adaptive lasso regression
. Mathematical Biosciences.
20. Alhamzawi, R. and Algamal, Z and Haithem T.M Ali (2018). Gene selection for microarray gene expression classification using Bayesian Lasso quantile regression. Computers in Biology and Medicine.
145-152.
21. Alhamzawi, R. and Algamal, Z(2017). Bayesian bridge quantile regression. Communications in
Statistics - Simulation and Computation. Accepted.
22. Rahim Alhamzawi (2017). Bayesian variable selection and coefficient estimation in heteroscedastic
linear regression models. Journal of applied statistics. Accepted.
23. Rahim Alhamzawi (2017). Inference with three-level prior distributions in quantile regression problems. Journal of Applied Statistics, 44, 1947 – 1959.
24. Alhamzawi, A. (2017). Bayesian tobit quantile regression with L1/2 penalty. Communication in
Statistics- Simulation and Computation. Accepted.
25. Rahim Alhamzawi (2017). The Bayesian Elastic Net Regression. Communication in Statistics- Simulation and Computation, 1–13.
26. Rahim Alhamzawi (2017). Bayesian quantile regression for ordinal longitudinal data. Journal of
Applied Statistics. Accepted.
27. Rahim Alhamzawi (2017). Web-based supplementary materials for “Bayesian Quantile Regression
for Ordinal Longitudinal Data". Journal of Applied Statistics. Accepted.
28. Alhamzawi, A. and Alhamzawi, R. (2016). Gravitational lensing in the strong field limit by modified
gravity. General Relativity and Gravitation, 48(12), 167.
29. Rahim Alhamzawi (2016). Bayesian analysis of composite quantile regression. Statistics in Biosciences,
8(2), 358-373.
Rahim Alhamzawi 4
30. Rahim Alhamzawi (2016). Bayesian model selection in ordinal quantile regression. Computational
Statistics & Data Analysis, 103, 68–78.
31. Taha Alshaybaweeab, Habshah Midi, Rahim Alhamzawi (2016). Bayesian elastic net single index
quantile regression. Journal of Applied Statistics, 44(5), 853–871.
32. Keming Yu, Xi Liu, Rahim Alhamzawi, Frauke Becker, and Joanne Lord (2016). Statistical methods
for body mass index: A selective review. Statistical Methods in Medical Research. Accepted.
33. Alhamzawi, A. and Alhamzawi, R. (2015). Gravitational lensing by f(R, T) gravity. International
Journal of Modern Physics D, 25(02), 1650020.
34. Alhamzawi, A. and Alhamzawi, R. (2015). Circular orbits in modified gravity. Astrophysics and Space
Science, 358(2), 50.
35. Hashem, H., Vinciotti, V., Alhamzawi, R. and Yu, K. (2015). Quantile regression with group Lasso
for classification. Advances in Data Analysis and Classification, 10(3), 375-390.
36. Alhamzawi, R. (2015). Model selection in quantile regression models. Journal of Applied Statistics, 42,
445–458.
37. Alhamzawi, R. and Yu, K. (2014). Bayesian Tobit quantile regression using g-prior distribution with
ridge parameter. Journal of Statistical Computation and Simulation. 85, 2903–2918.
38. Alhamzawi, R. (2014). Bayesian elastic net Tobit quantile regression. Communications in Statistics -
Simulation and Computation, 45(7), 2409-2427.
39. Yu, K., Dang, W., Zhu, H. and Alhamzawi, R. (2013). Comment on Article by Spokoiny, Wang and
Ha¨rdle. Journal of Statistical Planning and Inference. 143: 1140–1144.
40. Alhamzawi, R. and Yu, K. (2013). Conjugate priors and variable selection for Bayesian quantile
regression. Computational Statistics and Data Analysis. 64: 209–219.
41. Benoit, D., Alhamzawi, R. and Yu, K. (2013). Bayesian Lasso Binary Quantile regression. Computational Statistics. 28: 2861-2873.
42. Alhamzawi, R. (2013). Tobit Quantile Regression with the adaptive Lasso penalty. The Fourth
International Arab Conference of Statistics. Accepted Oct 2013.
43. Alhamzawi, R. and Yu, K. (2012). Bayesian Lasso mixed quantile regression. Journal of Statistical
Computation and Simulation. 84, 868U˝ 880.
44. Alkenani, A., Alhamzawi, R., & Yu, K. (2012). Penalized Flexible Bayesian Quantile Regression.
Applied Mathematics, 3, 2155–2168.
45. Alhamzawi, R. and Yu, K. and Benoit, D. (2012). Bayesian adaptive Lasso quantile regression. Statistical Modelling, 12: 279-297.
46. Alhamzawi, R. and Yu, K. (2012). Variable selection in quantile regression via Gibbs sampling.
Journal of Applied Statistics, 39: 799-813.
47. Alhamzawi, R., Yu, K., Vinciotti, V. and Tucker, A. (2011). Prior elicitation for mixed quantile regression with an allometric model. Environmetrics, 22: 911-920.
48. Alhamzawi R, Yu, K., Pan, J. (2011). Prior Elicitation in Bayesian Quantile Regression for Longitudinal Data. J Biomet Biostat 2:115.
49. Alhamzawi, R. and Yu, K. (2011). Power Prior Elicitation in Bayesian Quantile Regression. Journal of
Probability and Statistics, vol. 2011, Article ID 874907, 16 pages, 2011.
Rahim Alhamzawi 5
Papers Under Review
1. Mallick, H., Alhamzawi, R., & Svetnik, V. (2020). The Reciprocal Bayesian LASSO. arXiv preprint
arXiv:2001.08327.
2. Mallick, H., Alhamzawi, R. (2020). The Reciprocal Elastic Net.
3. Alhamzawi, R. (2020). The Reciprocal Bayesian Bridge for left-censored data.
Computer Skills
1. FORTRAN
2. Mathematica
3. MATLAB
4. SPSS
5. LATEX
6. The R Project for Statistical Computing
R Softwares
(a) Mallick H, Alhamzawi R, Svetnik V. (2019). BayesRecipe: Bayesian Reciprocal Regularization .
(b) Alhamzawi, R. (2019). Brq: Bayesian analysis of quantile regression models. R package version
1.0.
(c) Benoit, D., Alhamzawi, R., Yu, K., Poel, D. V. (2013). bayesQR: Bayesian quantile regression. R
package version 2.1.
(d) Alhamzawi, R. (2012). Aelasticnet: Bayesian Adaptive Elastic-Net for high dimensional sparse
quantile regression models. R package version 2.13.1.
Mathematica Software
(a) Alhamzawi, A. and Alhamzawi, R (2014). ATA: Advanced Tensor Analysis. Mathematica
package.
Recent Talks and Posters
i. Alhamzawi, R. (2019). A new Bayesian group lasso probit regression. International Conference on Data Science, Machine Learning and Statistics - 2019. Yil University, 65080 Van,
Turkey.
ii. Alhamzawi, R. (2013). Modification of Elastic Net in High-Dimensional Poisson Regression
Model. The Fourteenth International Conference of Statistics, Iraqi Statistical Association.
Al Mansour Hotel - Baghdad. Al Rasheed Baghdad Hotel.
iii. Alhamzawi, R. (2013). Tobit Quantile Regression with the adaptive Lasso penalty. The
Fourth International Arab Conference of Statistics. Al Rasheed Baghdad Hotel.
Rahim Alhamzawi 6
iv. Alhamzawi, R. (2013). Bayesian Tobit quantile regression using g-prior distribution with
ridge parameter. YSM2013, UK. Imperial College London. 4th–5th July 2013, UK.
v. Alhamzawi, R. (2013). Bayesian subset selection for fixed and random effects in quantile
regression models. YSM2013. Imperial College London. 4th–5th July 2013, UK.
vi. Alhamzawi, R.(2013). Bayesian Quantile Regression. Day on Quantile Regression at the
Royal Statistical Society U London, ˝ 29 May, UK.
vii. Alhamzawi, R. and Yu, K. (2012). Bayesian censored quantile regression using g-prior.
Young Statisticians’ Meeting. 2nd - 3rd April 2012. University of Cambridge, UK.
viii. Alhamzawi, R. (2011). Young Researchers in Mathematics. The University of Warwick, UK.
ix. Alhamzawi, R. and Yu, K. (2010). Prior elicitation in mixed quantile regression models. 3rd
International Conference of the ERCIM WG on COMPUTING & STATISTICS (ERCIM’10),
Senate House, University of London, UK.
Professional Activities
Editor-in-Chief
1. AL-Qadisiyah Journal For Administrative and Economic sciences
Lead Guest Editor
1. Special Issue: Quantile Regression and Beyond in Statistical Analysis of the Data
2. Special Issue: Modeling and Applications of Regularized Regression
Editorial Conference
1. The 1st International Scientific Conference on Pure Science. Editor for Mathematics section.
Editorial Board
1. Eastern European Business and Economics Journal
2. Journal of Computation and Mathematics (USA)
3. Journal of Mathematical Modeling (USA)
4. Journal of Biomedical Materials Research (USA)
Reviewer
1. Statistical Modelling
2. Journal of the Korean Statistical Society
3. Computational Statistics & Data Analysis
4. Bayesian Analysis
5. Statistics & Probability Letters
6. BMC Medical Research Methodology
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7. Journal of Statistical Computation and Simulation
8. Journal of Applied Statistics
9. Journal of Computation and Mathematics
10. Journal of Mathematical Modeling
11. Journal of Biomedical Materials Research
12. Hacettepe Journal of Mthematics and Statistics
13. JSciMed Central
14. Journal of Probability and Statistics
15. Journal of Chemometrics
Teaching
Brunel University (United Kingdom)
Mathematics for Economics (EC1005 level one modules): (2010-2011), (2011-2012), (2012-2013).
Statistics III (MA3970 Module): (2010-2011), (2011-2012).
Essential Skills: (2010-2011), (2011-2012).
Statistics II (MA2770 Module): (2011-2012).
Probability: (2011-2012).
Statistics: (2011-2012).
Al-Qadisiyah University
Statistics, Computer Programming (2000-2008).
Operation Research (2000-2007).
Stochastic Process, Simulations (2006-2008).
Statistical Inference, Time Series Analysis (2002-2004).
Multivariate, Linear Algebra (2000-2001).
Design and Analysis of Experiments (1999-2004).
Regression Analysis (2002-2004).
Mathematics (2000-2006).
Rahim Alhamzawi 8
Acknowledgements
1. Acknowledgement from Cogent Mathematics -Taylor & Francis. Reviewer acknowledgement.
2. Acknowledgement from BMC Medical Research Methodology, 2013. Reviewer acknowledgement.
3. Acknowledgement from Journal of Applied Statistics, 2010-2011. Reviewer acknowledgement.
Last updated: August 12, 2022