Publications

The full list, with citations, is on Google Scholar.

Journal articles

Deep learning embedded latent class joint modelling of time-to-event and longitudinal data

Harris, T. J. E., Nakhaei Rad, N., & Skhosana, S. B. (2026). Statistical Methods in Medical Research.

DOI
Model-based clustering using a new mixture of circular regressions

Skhosana, S. B., & Nakhaei Rad, N. (2026). Advances in Data Analysis and Classification.

DOI Code
A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions

Skhosana, S. B., Millard, S. M., & Kanfer, F. H. J. (2024). Statistics and Computing, 34(4), 125.

DOI Code
A novel EM-type algorithm to estimate semi-parametric mixtures of partially linear models

Skhosana, S. B., Millard, S. M., & Kanfer, F. H. J. (2023). Mathematics, 11(5), 1087.

DOI
Fitting non-parametric mixture of regressions: Introducing an EM-type algorithm to address the label-switching problem

Skhosana, S. B., Kanfer, F. H. J., & Millard, S. M. (2022). Symmetry, 14(5), 1058.

DOI

Shifted asymmetric Laplace mixtures of experts

Skhosana, S. B., & Nguyen, H. D. (2026). arXiv preprint, arXiv:2605.02012.

arXiv
Economic complexity and environmental impact using a neural-network embedded semiparametric mixture of experts model

Skhosana, S. B., Olaniran, A. O., Nakhaei Rad, N., & Gupta, R. (2026). University of Pretoria, Department of Economics Working Paper Series, No. 202618.
Nonparametric contaminated Gaussian mixture of regressions

Skhosana, S. B., & Yao, W. (2026). arXiv preprint, arXiv:2601.06695.

arXiv Code
Robust semi-parametric mixtures of linear experts using the contaminated Gaussian distribution

Mambondimumwe, P., Skhosana, S. B., & Nakhaei Rad, N. (2026). arXiv preprint, arXiv:2601.12425.

arXiv Code

A new approach to estimate semi-parametric Gaussian mixtures of regressions with varying mixing proportions

Skhosana, S. B., Millard, S. M., & Kanfer, F. H. J. (2024). Statistical Modeling and Applications: Multivariate, Heavy-Tailed, Skewed Distributions and Mixture Modeling, Volume 2, pp. 149–175.

DOI