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Statistics (Live Theses) 
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Statistics (Scholarly Publications) 
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Statistics (Theses and Dissertations)
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Learning Mixtures of Gaussian Processes through Random Projection
(2024)We propose an ensemble clustering framework to uncover latent cluster labels in functional data generated from a Gaussian process mixture. Our method exploits the fact that the projection coefficients of the functional ... 
Statistical Methods to Extrapolate TimeToEvent Data
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2024)This thesis investigates methods used to predict longterm survival of observations (typically survival times) beyond the time at which data followup is available. Current practice is to use parametric survival models; ... 
Bayesian Tree Regression within a Streaming Context
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2023)Regression in a statistical streaming environment. Explore either large amounts of data or data that is continually being generated in a meaningful way. The streaming setting is challenging because either the proportion ... 
A Theoretical Analysis of Density Peaks Clustering and the Componentwise PeakFinding Algorithm
(2024)Density peaks clustering detects modes as points with high density and large distance to points of higher density. Each nonmode point is assigned to the same cluster as its nearest neighbor of higher density. Density ... 
Distributed Lag Regression Methods and Compartmental Models for Analysis of Disease Progression
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2023)ANCA vasculitis is an autoimmune disease characterised by relapses, or flares, that can have a severe detrimental impact on patient health. Flares can be prevented by suppressing the immune system but this exposes the ... 
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2023)Ignorance within noncooperative games, reflected as a player's uncertain preferences towards a game's outcome, is examined from a probabilistic point of view. This topic has had scarce treatment in the literature, which ... 
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models
(2023)Methods that employ the EM algorithm for parameter estimation typically face the notorious yet unsolved problem that the initialization input significantly impacts the algorithm output. We here develop a Reinforced ... 
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach
(2023)Ignorance within noncooperative games, reflected as a player’s uncertain prefer ences towards a game’s outcome, is examined from a Bayesian point of view. This topic has had scarce treatment in the literature, which ... 
Consistent ModeFinding for Parametric and NonParametric Clustering
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2022)Density peaks clustering detects modes as points with high density and large distance to points of higher density. To cluster the observed samples, points are assigned to the same cluster as their nearest neighbor of higher ... 
Effect of plant diversity and drought on the agronomic performance of intensively managed grassland communities
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2022)Temperate agroecosystems are crucial for food production and financially important for the rural economy, but can have strong environmental impacts and are threatened by increased frequency of extreme weather events. Over ... 
Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process
(2022)The generalized inverse Gaussian (GIG) Lévy process is a limit of compound Poisson processes, including the stationary gamma process and the stationary inverse Gaussian process as special cases. However, fitting the GIG ... 
DCF: An Efficient and Robust DensityBased Clustering Method
(2021)Densitybased clustering methods have been shown to achieve promising results in modern data mining applications. A recent approach, Density Peaks Clustering (DPC), detects modes as points with high density and large ... 
Semantic image segmentation based on spatial relationships and inexact graph matching
(2020)We propose a method for semantic image segmentation, combining a deep neural network and spatial relationships between image regions, encoded in a graph representation of the scene. Our proposal is based on inexact graph ... 
An Integrated Framework for Estimating the Number of Classes with Application for Species Estimation
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2021)The two most common approaches for estimating the number of distinct classes within a population are either to use sampling data directly with combinatorial arguments or to extrapolate historical discovery data. However, ... 
Image Restoration Using Deep Learning
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)In this thesis, we propose several convolutional neural network (CNN) architectures with fewer parameters compared to stateoftheart deep structures to restore original images from degraded versions. Employing fewer ... 
A Heuristic Policy for Maintaining Multiple MultiState Systems
(2020)This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multistate systems, and the dynamic of each multistate system is modelled by a Markov chain. Determining ... 
Matchingadjusted indirect comparisons: identifying method variations and implementing models in R
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)In the framework of evidencebased medicine, comparative effectiveness research is a fundamental activity to the development of pharmaceutical products and medical treatments. For a given medical condition, several competing ... 
Efficient and scalable inference for generalized student  T process models
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)Gaussian Processes are a popular, nonparametric modelling framework for solving a wide range of regression problems. However, they are suffering from 2 major shortcomings. On the one hand, they require efficient, approximate ... 
Competing risks of default and prepayment of mortgage market
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)Using a large data set on the Single family home loans from The Federal Home Loan Mortgage Corporation (FHLMC), sponsored by the US government, this research studies the economic factors affecting the competing risks of ...