Now showing items 22-41 of 44

    • Image Restoration Using Deep Learning 

      ALBLUWI, FATMA HAMED (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 state-of-the-art deep structures to restore original images from degraded versions. Employing fewer ...
    • The Impact of Performing a Network Meta-Analysis with Imperfect Evidence 

      LEAHY, JOY (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2019)
      Network meta-analysis (NMA) is an important aspect of evidence synthesis in a clinical setting, as it allows us to compare treatments which may not have been analysed in the same trial. In an ideal scenario we would have ...
    • Importance resampling MCMC : a methodology for cross-validation in inverse problems and its applications in model assessment 

      Bhattacharya, Sourabh (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005)
      This thesis presents a methodology for implementing cross-validation in the context of Bayesian modelling of situations we loosely refer to as 'inverse problems'. It is motivated by an example from palaeoclimatology in ...
    • Improving exploration of posterior distributions in spatial models - a Markov chain Monte Carlo approach 

      Hayes, Bridette Anne-Marie (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006)
      A Markov chain Monte Carlo (MCMC) algorithm is proposed for the evaluation of a posterior distribution. The posterior distribution is from a model that has a spatial structure and exhibits many characterisics which are ...
    • Incorporating Ignorance within Game Theory: An Imprecise Probability Approach 

      Fares, Bernard (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2023)
      Ignorance within non-cooperative 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 ...
    • An Integrated Framework for Estimating the Number of Classes with Application for Species Estimation 

      Al-Ghamdi, Asmaa (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, ...
    • L_ Inference for shape parameter estimation 

      Arellano Vidal, Claudia L. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2014)
      In this thesis, we propose a method to robustly estimate the parameters that controls the mapping of a shape (model shape) onto another (target shape). The shapes of interest are contours in the 2D space, surfaces in the ...
    • Matching-adjusted indirect comparisons: identifying method variations and implementing models in R 

      CASSIDY, OWEN CHRISTOPHER (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)
      In the framework of evidence-based medicine, comparative effectiveness research is a fundamental activity to the development of pharmaceutical products and medical treatments. For a given medical condition, several competing ...
    • MCMC for inference on phase-type and masked system lifetime models 

      Aslett, Louis J.M. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2012)
      Common reliability data consist of lifetimes (of censoring information) on all components and systems under examination. However, masked system lifetime data represents an important class of problems where the information ...
    • Modelling the distribution of grouped survival data via dependant neutral-to-the-right priors 

      DONAGHY, FEARGHAL (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)
      With each update of its browser, Firefox receives reports of the time of discovery of a large number of bugs associated with that update. This process yields survival data which is separated by update into groups and often ...
    • Modelling Uncertainty and Vagueness within Recommender Systems via Nonparametric Predictive Inference 

      MCCOURT, ANGELA (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2019)
      The way in which we learn is the subject of considerable research within multiple disciplines. There is also a vast amount of on-line material available to us, causing decision-making to become increasingly difficult. ...
    • Reliability updating in linear opinion pooling for multiple decision makers 

      Bolger, Donnacha (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2016)
      Accurate information sources are vital prerequisites for good decision making. In this thesis we consider a multiple participant setting, where all decision makers (DMs) have a collection of neighbours with whom they share ...
    • Spatial modelling of damage accumulation in bone cement 

      Heron, Elizabeth A. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005)
      In this thesis we develop spatial models for damage accumulation in the bone cement of hip replacement specimens. A total hip replacement consists of an artificial cup, forming the socket portion of the joint, and a ...
    • Statistical framework for multi sensor fusion and 3D reconstruction 

      Ruttle, Jonathan (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2012)
      Multi-view 3D reconstruction is an area of computer vision where multiple images are taken of an object and information in those images is used to generate a 3D model describing the shape and size of that object. The ...
    • Statistical Methods to Extrapolate Time-To-Event Data 

      Cooney, Philip (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2024)
      This thesis investigates methods used to predict long-term survival of observations (typically survival times) beyond the time at which data follow-up is available. Current practice is to use parametric survival models; ...
    • Statistical models for food authenticity 

      Toher, Deirdre Ann (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2009)
      The authentication of food samples pose a particular problem for regulators. The routine testing of premium food products, most likely to be subject to manipulation for commercial gain, is only feasible if the testing ...
    • The development of theory to assist the application of destination yield management 

      Mulvey, Michael F. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005)
      Destinations are geographical spaces where tourism experiences take place. They include the built and natural environm ent, attractions, the host community and commercial interests - predominantly SMEs. The role of ...
    • Topics in unsupervised learning 

      McNicholas, Paul David (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2007)
      Two topics in unsupervised learning are reviewed and developed; namely, model-based clustering and association rule mining. A new family of Gaussian mixture models, with a parsim onious covariance structure, is introduced. ...
    • Tracking the distribution of bugs across software release versions 

      Ó Ríordáin, Seán (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2015)
      Real software systems always contain bugs and the question on every release manager’s mind coming up to a release centres around how many undiscovered bugs there still remain. This work looks at one model, (Goel and ...
    • Univariate time series modelling and forecasting using TSMARS 

      Keogh, Gerard (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006)
      This thesis studies threshold nonlinearity in time series using TSMARS, a time series extension of the Multivariate Adaptive Regression Splines (MARS) procedure of Friedman (1991a). MARS is model free and can detect and ...