1 citations · 4 across the 16 of their papers we have counts for
4 papers · 1 filter
Sleep pattern profiling using a finite mixture of contaminated multivariate skew-normal distributions on incomplete data
Jason Pillay, Cristina Tortora, Antonio Punzo +1
Medical data often exhibit characteristics that make cluster analysis particularly challenging, such as missing values, outliers, and cluster features like skewness. Typically, suc…
Clustering data with values missing at random using scale mixtures of multivariate skew-normal distributions
Jason Pillay, Cristina Tortora, Antonio Punzo +1
Handling missing data is a major challenge in model-based clustering, especially when the data exhibit skewness and heavy tails. We address this by extending the finite mixture of…
Mixtures of multivariate linear asymmetric Laplace regressions with multiple asymmetric Laplace covariates
Arnoldus F. Otto, Andriëtte Bekker, Antonio Punzo +2
In response to the challenge of accommodating non-Gaussian behaviour in data, the shifted asymmetric Laplace (SAL) cluster-weighted model (SALCWM) is introduced as a model-based me…
Modeling Bounded Count Environmental Data Using a Contaminated Beta-Binomial Regression Model
Arnoldus F. Otto, Antonio Punzo, Johannes T. Ferreira +3
This paper investigates two environmental applications related to climate change, where observations consist of bounded counts. The binomial and beta-binomial (BB) models are commo…