Unsupervised Classification with a Family of Parsimonious Contaminated Shifted Asymmetric Laplace Mixtures
P McLaughlin, BC Franczak, AB Kashlak - Journal of Classification, 2024 - Springer
A family of parsimonious contaminated shifted asymmetric Laplace mixtures is developed for
unsupervised classification of asymmetric clusters in the presence of outliers and noise. A …
unsupervised classification of asymmetric clusters in the presence of outliers and noise. A …
Alternative skew Laplace scale mixtures for modeling data exhibiting high-peaked and heavy-tailed traits
The search and construction of appropriate and flexible models for describing and modelling
empirical data sets incongruent with normality retains a sustained interest. This paper …
empirical data sets incongruent with normality retains a sustained interest. This paper …