2017/11/04 by Murray, Paula M., Browne, Ryan P., McNicholas, Paul D. · 1 citation
#Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME)
paper · doi:10.48550/arxiv.1711.01504
The mixture of factor analyzers model was first introduced over 20 years ago and, in the meantime, has been extended to several non-Gaussian analogues. In general, these analogues account for situations with heavy tailed and/or skewed clusters. An approach is introduced that unifies many of these approaches into one very general model: the mixture of hidden truncation hyperbolic factor analyzers (MHTHFA) model. In the process of doing this, a hidden truncation hyperbolic factor analysis model is also introduced. The MHTHFA model is illustrated for clustering as well as semi-supervised classification using two real datasets.