Probability & Statistics:
Research in Probability and Statistics at McMaster is highly interdisciplinary, and reaches beyond the department into the Faculties of Science, Medical, Engineering and Business. Research interests include: Theoretical Probability (large deviations, stochastic differential equations, martingales) Applied Probability (stochastic genetics, queueing systems) and Mathematical Statistics (inferential methods, model-validity, outliers, multivariate analysis) and Applied Statistics (environmental hazards, animal abundance, genetics, climatology, pharmaceutics, and mortality).
Faculty in Probability & Statistics:
- Narayanaswamy Balakrishnan - Order statistics, distribution theory
- Angelo Canty - Computational statistics
- Aaron Childs - Statistical Inference, order statistics, outliers
- Shui Feng - Stochastic processes, interacting particle systems
- Fred M. Hoppe - Stochastic models, genetics and medicine, probability bounds
- Paul McNicholas - Classification, clustering, computational statistics, data science, machine learning, mixture models
- Sharon McNicholas - Data science, evolutionary algorithms, high-dimensional problems, machine learning, mixture models.
- Roman Viveros-Aguilera - Statistical Inference, reliability, discrete modeling