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 ...

Journal of Agricultural, Biological, and Environmental Statistics, Vol. 22, No. 4 (December 2017), pp. 585-601 (17 pages) We present a Bayesian nonparametric modeling approach to inference and risk ...

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 ...

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

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 ...