39 citations · 90 across the 7 of their papers we have counts for
8 papers
Quantifying Distances Between Clusters with Elliptical or Non-Elliptical Shapes
Meredith L. Wallace, Lisa McTeague, Jessica L. Graves +4
Finite mixture models that allow for a broad range of potentially non-elliptical cluster distributions is an emerging methodological field. Such methods allow for the shape of the…
INSPIRE: INvestigating Stellar Population In RElics II. First Data Release (DR1)
C. Spiniello, C. Tortora, G. D'Ago +12
The INvestigating Stellar Population In RElics is an on-going project targeting 52 ultra-compact massive galaxies at 0.1<z<0.5 with the X-Shooter@VLT spectrograph (XSH). These obje…
Cluster analysis and outlier detection with missing data
Hung Tong, Cristina Tortora
A mixture of multivariate contaminated normal (MCN) distributions is a useful model-based clustering technique to accommodate data sets with mild outliers. However, this model only…
Multiple Scaled Contaminated Normal Distribution and Its Application in Clustering
Antonio Punzo, Cristina Tortora
The multivariate contaminated normal (MCN) distribution represents a simple heavy-tailed generalization of the multivariate normal (MN) distribution to model elliptical contoured s…
A Mixture of Coalesced Generalized Hyperbolic Distributions
Cristina Tortora, Brian C. Franczak, Ryan P. Browne +1
A mixture of multiple scaled generalized hyperbolic distributions (MMSGHDs) is introduced. Then, a coalesced generalized hyperbolic distribution (CGHD) is developed by joining a ge…
Unsupervised Learning via Mixtures of Skewed Distributions with Hypercube Contours
Brian C. Franczak, Cristina Tortora, Ryan P. Browne +1
Mixture models whose components have skewed hypercube contours are developed via a generalization of the multivariate shifted asymmetric Laplace density. Specifically, we develop m…
A Mixture of Generalized Hyperbolic Factor Analyzers
Cristina Tortora, Paul D. McNicholas, Ryan P. Browne
Model-based clustering imposes a finite mixture modelling structure on data for clustering. Finite mixture models assume that the population is a convex combination of a finite num…
Factor PD-Clustering
Mireille Gettler Summa, Francesco Palumbo, Cristina Tortora
Factorial clustering methods have been developed in recent years thanks to the improving of computational power. These methods perform a linear transformation of data and a cluster…