Statistics: Recent submissions
Now showing items 1-20 of 132
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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 Time-To-Event Data
(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; ... -
A Theoretical Analysis of Density Peaks Clustering and the Component-wise Peak-Finding Algorithm
(2024)Density peaks clustering detects modes as points with high density and large distance to points of higher density. Each non-mode point is assigned to the same cluster as its nearest neighbor of higher density. Density ... -
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach
(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 ... -
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 non-cooperative 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 ... -
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 Density-Based Clustering Method
(2021)Density-based 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 ... -
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 state-of-the-art deep structures to restore original images from degraded versions. Employing fewer ... -
A Heuristic Policy for Maintaining Multiple Multi-State Systems
(2020)This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multi-state systems, and the dynamic of each multi-state system is modelled by a Markov chain. Determining ... -
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 ...