Undoubtedly, statistics has become one of the most important subjects in the modern world, where its applications are ubiquitous. The importance of statistics is not limited to statisticians, but also impacts upon non-statisticians who have to use statistics within their own dis…
"68" Result
Sort By:
Understanding the ways in which practitioners can identify and manage undernutrition is important within developing world countries. There is still much uncertainty when it comes to understanding which measures of undernutrition are the most effective predictors of adverse outco…
In any actual forecast, the future evolution of the system is uncertain and the forecasting model is mathematically imperfect. Both, ontic uncertainties in the future (due to true stochasticity) and epistemic uncertainty of the model (reflecting structural imperfections) complica…
The thesis examines the philosophical and foundational significance of Cohen's Independence results. A distinction is made between the mathematical and logical analyses of the "set" concept. It is argued that topos theory is the natural generalization of the mathematical theory …
Psychiatric distress, smoking and excessive alcohol consumption are common health problems which often occur together and are patterned by socioeconomic position. Smoking and drinking behaviours and mental health problems tend to develop over the transition from adolescence to a…
Flowgraph models are directed graph models for describing the dynamic changes in a stochastic process. They are one class of multistate models that are applied to analyse time-to-event data. The main motivation of the flowgraph models is to determine the distribution of the total…
The problem of earthquake risk assessment and management in insurance is a challenging one at the interface of geophysics, engineering seismology, stochastics, insurance mathematics and economics. In this work, I propose stochastic models and methods for the assessment of earthq…
A decision maker, when facing a decision problem, often considers several models to represent the outcomes of the decision variable considered. More often than not, the decision maker does not trust fully any of those models and hence displays ambiguity or model uncertainty aver…
Physical processes such as the weather are usually modelled using nonlinear dynamical systems. Statistical methods are found to be difficult to draw the dynamical information from the observations of nonlinear dynamics. This thesis is focusing on combining statistical methods wi…
Stochastic processes are mathematical objects that offer a probabilistic representation of how some quantities evolve in time. In this thesis we focus on estimating the trajectory and parameters of dynamical systems in cases where only indirect observations of the driving stocha…
This thesis aims to identify causal effects using a natural experimental approach. We focus on the Great Hanshin-Awaji Earthquake in midwestern Japan as a source of exogenous variation in the variables of interest. Chapter 1 explores the causal effect of schooling on juvenile de…
This PhD uses statistical analysis and qualitative interviews to analyse behaviour patterns in the context of causal theories of sexual offending and desistance from it, with a particular emphasis on socio-cultural reasons why people offend, stop offending, or offend at differen…
Latent variable models are widely used in social sciences in which interest is centred on entities such as attitudes, beliefs or abilities for which there e)dst no direct measuring instruments. Latent modelling tries to extract these entities, here described as latent (unobserve…
Estimating the size of an insect pest population in an agricultural field is an integral part of insect pest monitoring. An abundance estimate can be used to decide if action is needed to bring the population size under control, and accuracy is important in ensuring that the cor…
An essential aspect of survival analysis is the estimation and prediction of survival probabilities for individuals. For this purpose, mathematical modelling of the hazard rate function is a fundamental issue. This thesis focuses on the novel estimation and application of hazard…
Regression models for count data are usually based on the Poisson distribution. This thesis is concerned with Bayesian inference in more flexible models for count data. Two classes of models and algorithms are presented and studied in this thesis. The first employs a generalisat…
This study is concerned with the sexual abuse of enslaved women and girls by white men in the antebellum South. Interviews conducted by the Federal Writers’ Project in the 1930s are studied alongside nineteenth-century narratives of the formerly enslaved in order to make calcula…
Local polynomial regression has received a great deal of attention in the past. It is a highly adaptable regression method when the true response model is not known. However, estimates obtained in this way are not guaranteed to be monotone. In some situations the response is kno…
The thesis deals with the mirror and synchronous couplings of geometric Brownian motions, the policy improvement (or iteration) algorithm in completely continuous settings, and an application where the latter is applied to the former. First we investigate whether the mirror and …