Author

A. Bekker

3 papers indexed here

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Review Aug 2026

Handling mild outliers and unobserved values in compositional datasets using finite mixtures of mean-parametrised Dirichlet models

Heterogeneous compositional data may be simultaneously affected by missing values and atypical points, posing challenges for both clustering and outlier detection. We develop a mixture model for incomplete compositional data under Huber's contamination model, with contamination defined directly on the simplex and on ob...

J. Pillay, A. Bekker, C. Tortora et al. · 0 citations

Preprint Jul 2026

Handling Missingness and Censoring in Dirichlet Models

Likelihood-based inference for compositional data generally requires fully observed compositions, hindering the direct treatment of missing or censored components on the simplex. In this paper, we develop an expectation-maximisation (EM)-type algorithm for maximum likelihood estimation of the Dirichlet parameters in th...

J. Pillay, A. Bekker, C. Tortora et al. · 1 citation

Preprint Jul 2026

Handling Missingness and Censoring in Dirichlet Mixture Models

Incomplete compositional data analysis faces a fundamental limitation: likelihood-based methods for compositional models generally require fully observed compositions, making it difficult to accommodate missing or censored proportions directly on the simplex. Consequently, analysts often discard partially observed comp...

J. Pillay, A. Bekker, C. Tortora et al. · 0 citations