Faculty - Dr. Sévérien Nkurunziza

Research Interests

My area of expertise is Statistics and my main research interests are statistical inference, statistical modeling and applied probability. The main topics of my recent publications involve stochastic modeling and inference in some ecological and/or biological systems. Also, I contributed to some applied areas such as mathematical modeling in accounting and in public policy.

Supervision

I have supervised two undergraduate students working in statistical inference, R-software, regression analysis and their applications. Currently, I supervise graduate students who are working on more applied topics such as linear models, planning design experiment, modeling of some cyclic predator-prey systems… Ph.D. students may select to work with me in topics such as statistical inference, asymptotic theory in statistics and applied probability.

Recent Publications

• Ghannam, M., and Nkurunziza, S. (2023). Change-point Detection in a Tensor Regression Model. TEST (Accepted).
• Ghannam, M., and Nkurunziza, S. (2023). Tensor Stein-rules in a Generalized Tensor Regression Model. Journal of Multivariate Analysis (Accepted).
• Lyu, Y., and Nkurunziza, S. (2023). Inference in Generalized Exponential OU Processes with Change-point. Statistical Inference for Stochastic Processes(Accepted).
• Lyu, Y., and Nkurunziza, S. (2023). Inference in Generalized Exponential O-U Processes. Statistical Inference for Stochastic Processes, Vol. 26, 581--618.
• Nkurunziza, S. (2023). On efficiency of some restricted estimators in a multivariate regression model. Statistical Papers, vol. 64, 617--642.
• Ghannam, M., and Nkurunziza, S. (2022). The risk of tensor Stein-rules in elliptically contoured distributions. Statistics, vol. 56 (2), 421--454.
• Ghannam, M., and Nkurunziza, S. (2022). Improved estimation in tensor regression with multiple change-points. Electronic Journal of Statistics, vol. 16 (2), 4162--4221.
• Nkurunziza, S. (2021). Inference problem in generalized fractional Ornstein-Uhlenbeck Processes with Change-Point. Bernoulli Journal, vol. 27 (1) 107--134.
• Nkurunziza, S., and Shen, L. (2020). Inference in a multivariate generalized mean-reverting process with a change-point. Statistical Inference for Stochastic Processes, vol. 23, 199--226.
• Chen, F., Mamon, R., and Nkurunziza, S. (2020). Inference for a change-point problem under an Ornstein-Uhlenbeck setting with unequal and unknown volatilities. The Canadian Journal of Statistics, vol. 48 (1), 62--78.
• Nkurunziza, S., and Fu, K. (2019). Improved inference in generalized mean-reverting processes with multiple change-points. Electronic Journal of Statistics, vol. 13 (1), 1400--1442.
• Chernoukhov, A, Hussein, A., Nkurunziza, S., and Bandyopadhyay, D. (2018). Bayesian inference in time-varying additive hazards models with applications to disease mapping. Environmetrics (Special Issue), vol. 29 (e2478), 1--10.
• Nkurunziza, S., and Zhang, P. P. (2018). Estimation and testing in generalized mean-reverting processes with change-point. Statistical Inference for Stochastic Processes, vol. 21, 1, 191--215.
• Chen, F., Mamon, R., and Nkurunziza, S. (2018). Inference for a change-point problem under a generalised Ornstein-Uhlenbeck setting. Annals of the Institute of Statistical Mathematics, vol. 70, 4, 807--853.
• Chen, F., and Nkurunziza, S. (2016). A class of Stein-rules in multivariate regression model with structural changes. Scandinavian Journal of Statistics, vol. 43, 1, 83-102.
• Chen, F., and Nkurunziza, S. (2015). Optimal method in Multiple Regression with Structural Changes. Bernoulli Journal, vol. 21, 4, 2217--2241.
• Chen, F, and Nkurunziza, S. (2014). Constrained Inference in Multiple Regression with Structural Changes. Statistics & Risk Modeling (formerly Statistics & Decisions) vol. 31, 3-4, 237--257.
• Nkurunziza, S., and Chen, F. (2013). On extension of some identities for the bias and risk functions in elliptically contoured distributions. Journal of Multivariate Analysis, vol. 122, 190–201.
• Nkurunziza, S. (2012). Shrinkage Strategies In Some Multiple Multi-factor Dynamical Systems. ESAIM: Probability and Statistics, Vol. 16, 139-150.
• Nkurunziza, S. (2011). Shrinkage Strategy In Stratified Random Sample Subject To Measurement Error. Statistics and Probability Letters, Vol. 81, 2, 317-325.
• Nkurunziza, S., and Ahmed, S. E. (2010). Shrinkage Drift Parameter Estimation for Multi-factor Ornstein-Uhlenbeck Processes. Applied Stochastic Models in Business and Industry, Vol. 26, 2, 103-124.
• Nkurunziza, S. (2010). Testing Concerning the Homogeneity of Some Predator-Prey Populations. Journal of Statistical Planning and Inference (JSPI), Vol. 140, 323-333

For full list of publications https://web2.uwindsor.ca/math/severien/research.html. 

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