1 citations · 1 across the 5 of their papers we have counts for
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Modelling and detecting mild and gross anomalies in circular data via double-contaminated models
Antonio Punzo, Andriëtte Bekker, Arno Otto +2
In this paper, we propose a model-based framework to robustify inference for circular data in the presence of anomalous observations, distinguishing between mild and gross anomalie…
Mean regression for (0,1) responses via beta scale mixtures
Arno Otto, Andriëtte Bekker, Johan Ferreira +1
To achieve a greater general flexibility for modeling heavy-tailed bounded responses, a beta scale mixture model is proposed. Each member of the family is obtained by multiplying t…
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…
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…
Spatio-temporal insights for wind energy harvesting in South Africa
Matthew de Bie, Janet van Niekerk, Andriette Bekker
Understanding complex spatial dependency structures is a crucial consideration when attempting to build a modeling framework for wind speeds. Ideally, wind speed modeling should be…