4 citations · 10 across the 18 of their papers we have counts for
8 papers · 1 filter
Modeling Frequency and Severity of Claims with the Zero-Inflated Generalized Cluster-Weighted Models
Nikola Pocuca, Petar Jevtic, Paul D. McNicholas +1
In this paper, we propose two important extensions to cluster-weighted models (CWMs). First, we extend CWMs to have generalized cluster-weighted models (GCWMs) by allowing modeling…
Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes
Forrest Paton, Paul D. McNicholas
Functional data analysis is a statistical framework where data are assumed to follow some functional form. This method of analysis is commonly applied to time series data, where ti…
An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering
Sharon M. McNicholas, Paul D. McNicholas, Daniel A. Ashlock
An evolutionary algorithm (EA) is developed as an alternative to the EM algorithm for parameter estimation in model-based clustering. This EA facilitates a different search of the…
Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers
Michael P. B. Gallaugher, Paul D. McNicholas
In recent years, data have become increasingly higher dimensional and, therefore, an increased need has arisen for dimension reduction techniques for clustering. Although such tech…
Parameter-wise co-clustering for high-dimensional data
M. P. B. Gallaugher, C. Biernacki, P. D. McNicholas
In recent years, data dimensionality has increasingly become a concern, leading to many parameter and dimension reduction techniques being proposed in the literature. A parameter-w…
Robust Model-Based Clustering of Voting Records
Yang Tang, Paul D. McNicholas, Antonio Punzo
We explore the possibility of discovering extreme voting patterns in the U.S. Congressional voting records by drawing ideas from the mixture of contaminated normal distributions. A…