The importance of robust variable selection and regularization as solutions to the collinearity influential
high leverage points’ adverse effects in a quantile regression (QR) setting cannot be overemphasized,
just as ...
Non-performing loans (NPLs) are detrimental to profits in the banking sector. Predicting the level of NPLs using macroeconomic variables is vital in order to build mitigating actions for such scenarios to safeguard the ...
Policy lapse is a vital component in life insurance as it affects future pricing and impacts the solvency of the life insurer. Accurate prediction of lapse will help the insurers to implement personalised retention strategies ...
The premise of this study is that price fluctuations amongst exchange rates, stock and
commodities markets are dynamically linked. The study models monthly price changes
amongst these markets in 20 highest World Bank ...
The underperforming agricultural sector in Sub-Saharan Africa (SSA) has left African countries with
insufficient food production in the face of challenges related to climate change, diseases and
increasing population ...
Nowadays human activities produce massive amounts of data everyday. It is estimated that 2.5
quintillions bytes of data are produced daily. The ability to analyse and interpret such data, usually
referred to as ‘big ...
Multivariate longitudinal ordinal data are collected for studying the dependence between
multivariate ordinal outcomes, the changes over time and associated determinant factors. This
emanates from the interdependence ...
The conventional approach in determining HIV risk factors fails to consider the influence behavioural and biological factors may have when modelled jointly. This study investigates the extent of influence behavioural and ...
If solar power is to be integrated into the national grid in large volumes, it should be backed up by accurate short-term solar irradiance forecasting information. This is because system de signers in the solar power markets ...
Double sampling procedure is adapted from a statistical branch called acceptance sampling. The first Shewhart-type double sampling monitoring scheme was introduced in the statistical process monitoring (SPM) field in 1974. ...
The objective of the study was to identify the factors that affect the survival lifetime of HIV+ terminal patients in rural district hospitals of Albert Luthuli municipality in the Mpumalanga province of South Africa. A ...
Copulas functions are a flexible tool for modelling the dependence structure between variables. The joint and marginal distributions of Copulas are not constrained by the assumptions of normality. This study examines the ...
Classic parametric statistical tests, like the analysis of variance (ANOVA), are powerful tools
used for comparing population means. These tests produce accurate results provided the data
satisfies underlying assumptions ...
South Africa is rich in platinum group metals (PGMs) and these metals are important in providing jobs as well as investments some of which have been seen in the Johannesburg Securities Exchange (JSE). In this country this ...
The term aggregation refers to overdispersion and both are used interchangeably in this thesis. In addressing the problem of prevalence of infectious parasite species faced by most rural livestock farmers, we model the ...
Unemployment in South Africa has continued to be consistently high as indicated by the various reports published by Statistics South Africa. Unemployment is a global problem where in Organisation for Economic Co-operation ...
This study uses aspects of time series methodology to model and forecast major taxes such as Personal Income Tax (PIT), Corporate Income Tax (CIT), Value Added Tax (VAT) and Total Tax Revenue(TTAXR) in the South African ...
Return on Capital Employed (ROCE) is a popular financial instrument and communication tool for the appraisal of companies. Often, companies management and other practitioners use untested rules and behavioural approach ...
Value-at-Risk (VaR) model fails to predict financial risk accurately especially during financial crises. This is mainly due to the model’s inability to calibrate new market information and the fact that the risk measure ...