5 papers
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…
A Contaminated Model for Overdispersed Multinomial Microbiome Count Data
Ockert van Heerden, Andriëtte Bekker, Seite Makgai +2
Multinomial count data, such as microbial composition profiles derived from sequencing studies, frequently contain anomalous observations that distort parameter estimates. The Diri…
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…
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…