Bayesian nonparametric mixture models represent a powerful statistical framework that extends traditional mixture modelling by allowing the number of mixture components to be inferred from the data ...

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 181, No. 3 (2018), pp. 635-647 (13 pages) Statistical agencies are increasingly adopting synthetic data methods for ...

We analyze a dataset arising from a clinical trial involving multi-stage chemotherapy regimes for acute leukemia. The trial design was a 2 × 2 factorial for frontline therapies only. Motivated by the ...

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...

You are invited to attend the following M.A.Sc. (Quality Systems Engineering) thesis examination. Data clustering is a fundamental unsupervised learning approach that impacts several domains such as ...