Finite mixture models and hidden Markov models (HMMs) occupy central roles in modern statistical inference and data analysis. Finite mixture models assume that data originate from a latent combination ...
In this paper, we introduce a Bayesian approach for clustering data using a sparse finite mixture model (SFMM). The SFMM is a finite mixture model with a large number of components k previously fixed ...
You are invited to attend the following M.A.Sc. (Information Systems Security) thesis examination. Clustering is an important step in data mining, machine learning, computer vision and image ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique Vol. 39, No. 3, A special issue of CJS in honour of Jack Kalbfleisch and Jerry Lawless / Un numéro spécial de la Revue ...
You are invited to attend the following M.A.Sc. (Quality Systems Engineering) thesis examination. Finite mixture models have been revealed to provide flexibility for data clustering. They have ...
This paper employs a statistical model recently developed by the author that combines a decomposition analysis of inequality with a finite mixture model that assumes multiple latent classes in the ...
In this paper, I revisit the controversy over the fundamental sources of comparative development. In contrast to much of the previous literature, my focus is on the appropriate specification of the ...