Prof Charl Pretorius
Uncertainty, structure and change: a non-parametric perspective...read more
Prof Charl Pretorius
Uncertainty, structure and change: a non-parametric perspective
Statistical methods help us navigate uncertainty when we are faced with data, offering structure in a world filled with noise. But how reliable are these methods, and how realistic are the assumptions upon which they are built? Furthermore, can we determine when the structure we believe in begins to change? This lecture explores these questions through the lens of non-parametric statistics, an approach that deliberately limits parametric assumptions and lets the data speak for itself. As concrete examples, I present several new procedures for detecting structural change in high-dimensional panel data – a type of multivariate time-series data commonly encountered in econometrics and finance. These detection procedures are non-parametric in the sense that they are valid for a broad class of popular models used in practical applications. A key idea that will be covered is how these procedures can be adapted to be self-normalising, in other words, so that the detection rules do not depend on nuisance parameters that are notoriously difficult to estimate without strong parametric assumptions. The procedures retain their favourable properties even in the presence of weak serial and cross-sectional dependence. These procedures are also extended to online detection procedures, where data arrives sequentially and structural changes must be identified in real time. While the methods are mathematically intricate, their purpose remains straightforward: to help distinguish actual effects from coincidental ones when uncertainty exists.
Prof Oriel Thekiso
No diagnostics, no disease control...read more
Prof Oriel Thekiso
No diagnostics, no disease control
Diagnosis is the first line of disease control, followed by treatment and management and once again diagnosis to monitor the success of the treatment. The same applies to prevention strategies, where diagnosis is conducted on a large scale through epidemiological studies, then prevention measures such as vaccinations and quarantines are applied. The success of prevention strategies is further monitored using diagnostic techniques. Observation of clinical signs and symptoms for any animal or human infection serves as the first step of a diagnosis. For laboratory diagnosis, microscopy remains the mainstay of diagnostic techniques. Serological assays that detect antibodies from plasma samples are also serving as routine diagnostic techniques especially for large-scale screening. The advent of DNA technology has revolutionised diagnostics, as DNA-based diagnostic assays are more specific and highly sensitive in order to detect infectious agents in humans and animals. My diagnostic research projects have focused on the adoption of loop-mediated isothermal amplification (LAMP) and polymerase chain reaction (PCR) for the diagnosis of various pathogens. As a result, together with various collaborators, I have developed DNA-based LAMP and PCR assays targeting specific gene fragments for the diagnosis of various animal and human diseases, including trypanosomosis, theileriosis, babesiosis, toxoplasmosis, Newcastle disease, bovine tuberculosis and brucellosis.