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Browsing Theses and Dissertations (Statistics) by Type "Mini Dissertation"
Now showing items 1-20 of 34
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(University of Pretoria, 2016)No abstract
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(University of Pretoria, 2022)The volume of big data increases daily. Big data poses challenges in storage, management, processing, analysis and visualisation. One technique of handling big data is the use of subset or sample that is good representation ...
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(University of Pretoria, 2021)The interest in the study and modeling of the strength within material science has continuously been of interest within engineering and the built environment, with the Weibull distribution frequently being the model of ...
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(University of Pretoria, 2017)In this mini-dissertation the importance of having an automated object classification procedure for classifying nanoparticles in nanoscale images (or referred to as nanoimages in this mini-dissertation) is discussed, and ...
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(University of Pretoria, 2021)The need for statistical tools capable of addressing high-dimensional data is ever-growing. One such tool is that of differential networks, which have become increasing popular within various branches of science. The ...
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(University of Pretoria, 2019-08)If a known distribution on a real line is given, it can be wrapped on the circumference of a unit circle. This research entails the study of a univariate skew-normal distribution where the skew-normal distribution is ...
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(University of Pretoria, 2017-06)Please read abstract in the document
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(University of Pretoria, 2022-12-07)Analysing unstructured data with minimal contextual information is a challenge faced in spatial applications such as movement data. Movement data are sequences of time-stamped locations of a moving entity analogous to text ...
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(University of Pretoria, 2017)In this mini-dissertation we briefly describe the context and development of spatial statistics, spatial sampling and point patterns. Thereafter spatial homogeneity is considered in detail. Before selecting an appropriate ...
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(University of Pretoria, 2016)This study emanates from a practical problem in the statistical process control (SPC) environment where the quality of a process is monitored. Speci cally, where the variance of a process is being assessed to be the same ...
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(University of Pretoria, 2022)The classification of molecules is of particular importance to the drug discovery process and several other use cases. Data in this domain can be partitioned into structural and sequence/text data. Several tech- niques ...
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(University of Pretoria, 2021)The skew-normal distribution was popularised by Azzalini [4] to model skewed data. However, the skew-normal distribution is always unimodal. Kundu [24] recently presented the geometric skew-normal distribution by considering ...
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(University of Pretoria, 2021)Due to tuberculosis (TB) being one of the top ten diseases in Africa with the highest mortality rate, a crucial objective is to find the appropriate medication to cure patients and prevent people from contracting the ...
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(University of Pretoria, 2020)Large volumes of text is being generated every minute which necessitates effective and robust tools to retrieve relevant information. Supervised learning approaches have been explored extensively for this task, but it is ...
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(University of Pretoria, 2020)Quantile estimation is a vital aspect of statistical analyses in a variety of fields. For example, lower quantile estimation is crucial to ensure the safety and reliability of wood-built structures. Various statistical ...
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(University of Pretoria, 2022-11-30)This mini-dissertation proposes constructing a family of spliced distributions at a point different from the median, hence k=1/4 instead of k=1/2, using the method of quantile splicing proposed by Mac'Oduol et al. (2020). ...
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(University of Pretoria, 2021)Longitudinal data refer to multiple observations collected on the same subject (or unit) over time. Zero-inflated data (containing many zeros) frequently occur, resulting in overdispersion in count data. Regression models ...
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(University of Pretoria, 2020-10)In a Biostatistics environment, the datasets to be analysed are frequently high-dimensional and multicollinearity is expected due to the nature of the features. However, many traditional approaches to statistical analysis ...
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(University of Pretoria, 2020)Copulas allow a joint probability distribution to be decomposed such that the marginals inform us about how the data were generated, separately from the copula which fully captures the dependency structure between the ...
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(University of Pretoria, 2020)Deep learning is a very popular field of research which can input a variety of data types [1, 16, 30]. It is a subfield of machine learning consisting of mostly neural networks. A challenge which is very commonly met in ...
Now showing items 1-20 of 34