4 papers
Robust model-based clustering via mixtures of multivariate pseudo-Voigt distributions
Babak F. Dehkordi, Jeffrey L. Andrews, Andrew Jirasek
We propose a multivariate extension of the pseudo-Voigt profile-a weighted convex combination of Gaussian and Cauchy distributions-within a finite mixture modeling framework for ro…
Mixtures of spatial factor analyzers for tensor-variate data
Hanzhang Lu, Keiran Malott, Kirsty Milligan +9
A mixture of spatial factor analyzers (MSFA) is introduced to address the challenges of clustering high-dimensional spatial data. By leveraging the underlying coordinate system, th…
Spatial Covariance Constraints for Gaussian Mixture Models
Hanzhang Lu, Keiran Malott, Venkat Suprabath Bitra +11
Although extensive research exists in spatial modeling, few studies have addressed finite mixture model-based clustering methods for spatial data. Finite mixture models, especially…
DEEPEAST technique to enhance power in two-sample tests via the same-attraction function
Yiting Chen, Min Gao, Wei Lin +3
Data depth has emerged as an invaluable nonparametric measure for the ranking of multivariate samples. The main contribution of depth-based two-sample comparisons is the introducti…