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Methodological and Computational Statistics

An essential component and prerequisite for conducting good research is statistical theory and methodology. In a more theoretical sense, postulating methodological frameworks for complex data remains of certain value by ensuring continuous development and enhancement of theory-based probabilistic models that may serve the said phenomena of random behaviour mathematically. In this focus area consideration and acknowledgment should be given to significant recent advancements in the statistical discipline.

Most significantly, processing power has increased rapidly; big data and more extensive multidimensional data systems can now be analysed. The science of statistics focuses on modelling and learning from data in both theoretical and applied settings. A more applied context calls these theoretical developments to action, with approaches many times requiring computationally challenging environments in which the modelling effort may be enriched with subsequent estimation and hypothesis testing. This focus area intends to unify fundamental methodological research in statistics together with computational aspects of the modern era.

Researchers

Andriette Bekker (UP) Focus Area Coordinator (FAC) andriette.bekker@up.ac.za
Johan Ferreira (UP) Assistant Focus Area Coordinator (AFAC) Johan.Ferreira@up.ac.za
Andriette Verster (UFS)
Alexander Muoka (UKZN)
Ali Ghodsi  (UWaterloo)
Aviwe Gqwaka (NMU)
Charles Chimedza (Wits)
Chritophe Ley (UGent)
Danielle Roberts (UKZN)
Frans Kanfer (UP)
Gary Sharp (NMU)
Henry Mwambi (UKZN)
Innocent Maposa (SU)
Innocent Mboya (UKZN)
Jan Beirlant (KU Leuven)
Jennifer Priestley (Kennesaw State University, USA)
Jesca Batidzirai (UKZN)
Johan Hugo (NMU)
Liz van der Merwe (UWC)
Maia Lesosky (UCT)
Marcello Pagano (Harvard)
Mina Norouzirad (NOVA University Lisbon)
Mohana Mohammed (UCT)
Najmeh Nakhaeirad (UP)
Nqayiya Awonke (NMU)
Priyanka Nagar (SU)
Seite Makgai (UP)
Sisa Pazi (NMU)
Tertius de Wet (SU)
Tony Ng (SMU)
Vijay Nair (UMich)
Warren Brettenny (NMU)
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