Doctoral Degrees (Statistics and Actuarial Science)
Recent Submissions
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Extreme quantile inference
(Stellenbosch : Stellenbosch University, 2020-03)ENGLISH SUMMARY : A novel approach to performing extreme quantile inference is proposed by applying ridge regression and the saddlepoint approximation to results in extreme value theory. To this end, ridge regression is ... -
Classifying yield spread movements in sparse data through triplots
(Stellenbosch : Stellenbosch University, 2020-03)ENGLISH SUMMARY : In many developing countries, including South Africa, all data that are required to calculate the fair values of financial instruments are not always readily available. Additionally, in some instances, ... -
Biplot methodology for analysing and evaluating missing multivariate nominal scaled data
(Stellenbosch : Stellenbosch University, 2019-12)ENGLISH ABSTRACT: This research aims at developing exploratory techniques that are specifically suitable for missing data applications. Categorical data analysis, missing data analysis and biplot visualisation are the ... -
Regularised Gaussian belief propagation
(Stellenbosch : Stellenbosch University, 2018-12)ENGLISH SUMMARY : Belief propagation (BP) has been applied as an approximation tool in a variety of inference problems. BP does not necessarily converge in loopy graphs and, even if it does, is not guaranteed to provide ... -
A statistical analysis of student performance for the 2000-2013 period at the Copperbelt University in Zambia
(Stellenbosch : Stellenbosch University, 2017-12)ENGLISH SUMMARY : Education in general, and tertiary education in particular are the engines for sustained development of a nation. In this line, the Copperbelt University (CBU) plays a vital role in delivering the ... -
Statistical inference of the multiple regression analysis of complex survey data
(Stellenbosch : Stellenbosch University, 2016-12)ENGLISH SUMMARY : The quality of the inferences and results put forward from any statistical analysis is directly dependent on the correct method used at the analysis stage. Most survey data analyzed in practice riginate ... -
Multivariate statistical process evaluation and monitoring for complex chemical processes
(Stellenbosch : Stellenbosch University, 2015-12)ENGLISH ABSTRACT: In this study, the development of an innovative fully integrated process monitoring methodology is presented for a complex chemical facility, originating at the coal feed from different mines up to the ... -
The identification and application of common principal components
(Stellenbosch : Stellenbosch University, 2014-12)ENGLISH ABSTRACT: When estimating the covariance matrices of two or more populations, the covariance matrices are often assumed to be either equal or completely unrelated. The common principal components (CPC) model ... -
Multi-label feature selection with application to musical instrument recognition
(Stellenbosch : Stellenbosch University, 2013-12)ENGLISH ABSTRACT: An area of data mining and statistics that is currently receiving considerable attention is the field of multi-label learning. Problems in this field are concerned with scenarios where each data case can ... -
Bayesian approaches of Markov models embedded in unbalanced panel data
(Stellenbosch : Stellenbosch University, 2012-12)ENGLISH ABSTRACT: Multi-state models are used in this dissertation to model panel data, also known as longitudinal or cross-sectional time-series data. These are data sets which include units that are observed across two ... -
Influential data cases when the C-p criterion is used for variable selection in multiple linear regression
(Stellenbosch : Stellenbosch University, 2003)ENGLISH ABSTRACT: In this dissertation we study the influence of data cases when the Cp criterion of Mallows (1973) is used for variable selection in multiple linear regression. The influence is investigated in terms ... -
Time series forecasting and model selection in singular spectrum analysis
(Stellenbosch : Stellenbosch University, 2002-11)ENGLISH ABSTRACT: Singular spectrum analysis (SSA) originated in the field of Physics. The technique is non-parametric by nature and inter alia finds application in atmospheric sciences, signal processing and recently ... -
Edgeworth-corrected small-sample confidence intervals for ratio parameters in linear regression
(Stellenbosch : Stellenbosch University, 2002-03)ENGLISH ABSTRACT: In this thesis we construct a central confidence interval for a smooth scalar non-linear function of parameter vector f3 in a single general linear regression model Y = X f3 + c. We do this by ... -
Extensions of biplot methodology to discriminant analysis with applications of non-parametric principal components
(Stellenbosch : Stellenbosch University, 2001)ENGLISH ABSTRACT: Gower and Hand offer a new perspective on the traditional biplot. This perspective provides a unified approach to principal component analysis (PCA) biplots based on Pythagorean distance; canonical ... -
Aspects of model development using regression quantiles and elemental regressions
(Stellenbosch : Stellenbosch University, 2007-03)ENGLISH ABSTRACT: It is well known that ordinary least squares (OLS) procedures are sensitive to deviations from the classical Gaussian assumptions (outliers) as well as data aberrations in the design space. The two major ... -
Statistical inference for inequality measures based on semi-parametric estimators
(Stellenbosch : Stellenbosch University, 2011-12)ENGLISH ABSTRACT: Measures of inequality, also used as measures of concentration or diversity, are very popular in economics and especially in measuring the inequality in income or wealth within a population and ... -
Improved estimation procedures for a positive extreme value index
(Stellenbosch : University of Stellenbosch, 2010-12)ENGLISH ABSTRACT: In extreme value theory (EVT) the emphasis is on extreme (very small or very large) observations. The crucial parameter when making inferences about extreme quantiles, is called the extreme value index ... -
Assessing the influence of observations on the generalization performance of the kernel Fisher discriminant classifier
(Stellenbosch : Stellenbosch University, 2008-12)Kernel Fisher discriminant analysis (KFDA) is a kernel-based technique that can be used to classify observations of unknown origin into predefined groups. Basically, KFDA can be viewed as a non-linear extension of Fisher’s ... -
Variable selection for kernel methods with application to binary classification
(Stellenbosch : University of Stellenbosch, 2008-03)The problem of variable selection in binary kernel classification is addressed in this thesis. Kernel methods are fairly recent additions to the statistical toolbox, having originated approximately two decades ago in ... -
A framework for estimating risk
(Stellenbosch : Stellenbosch University, 2008-03)We consider the problem of model assessment by risk estimation. Various approaches to risk estimation are considered in a uni ed framework. This a discussion of various complexity dimensions and approaches to obtaining bounds ...
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