Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 14 of 14 for “"Gaussian copula"”.
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Analysis off Dependent Discrete Choices Using Gaussian Copula
… the utilities. In this dissertation we use the Gaussian copula with compound symmetric and autoregressive of order one correlation matrices to construct a general multivariate model for the joint distribution of the utilities. The induced correlations on the utilities and the choice …
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Principal component analysis and classification of discrete and mixed feature datasets using Gaussian copula
… In this thesis, we proposed a model based on the Gaussian copula to perform dimensionality reduction and classification for datasets with purely discrete or mixed features. In Chapter 3, we developed a scale invariant and data contamination robust principal component analysis (PCA) for discrete …
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Analysis of Discrete Choice Probit Models with Structured Correlation Matrices
… choice models are presented using multivariate copulas. We presented a brief introduction of discrete choice copula models using the Gaussian copula and the Extreme value copula. Copula representations are useful in building multivariate distributions with several choices for marginals. The …
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Image Miner : an architecture to support deep mining of images
… on a subset of data. The worker uses a Gaussian Copula Process to tune parameters and determines the best set of parameters and model to use.
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Recent Advances in Bayesian Copula Models for Mixed Data and Quantile Regression
… and theoretical properties of the Bayesian Gaussian copula, and deploy these models in a variety of applications. Copula models link arbitrary univariate marginal distributions under a multivariate dependence structure to define a valid joint distribution for a random vector. By estimating …
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Some Recent Advances in Non- and Semiparametric Bayesian Modeling with Copulas, Mixtures, and Latent Variables
… first contribution is an extension of the Gaussian factor model to Gaussian copula factor models, which accommodate continuous and ordinal data with unspecified marginal distributions. I describe how this model is the most natural extension of the Gaussian factor model, preserving its …
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Supervised Classification Using Copula and Mixture Copula
… random variables. In this dissertation, we use copula densities to model class conditional distributions. Such types of densities are useful when the marginal densities of a pattern vector are not normally distributed. This type of models are also useful for a mixed discrete and continuous …
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Latent state space models for prediction
… extension is termed as the Latent State Space Copula Model. In the novel Latent State Space Copula Modelthe ECG, ABP signals are considered to be correlated and are modeled using a bivariate Gaussian copula with Weibull marginals generated by a hidden state. We assume that there are hidden …
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Copula-Based Zero-Inflated Count Time Series Models
… In this dissertation, we propose two classes of copula-based time series models for zero-inflated counts with the presence of covariates. Zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), and zero-inflated Conway-Maxwell-Poisson (ZICMP) distributed marginals of the counts will …
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Credit Risk Modeling and Analysis Using Copula Method and Changepoint Approach to Survival Data
… consists of two parts. The first part uses Gaussian Copula and Student's t Copula as the main tools to model the credit risk in securitizations and re-securitizations. The second part proposes a statistical procedure to identify changepoints in Cox model of survival data. The recent …
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Advanced Topics in Introductory Statistics
… as canonical correlation analysis (CCA) and the Gaussian copula model. The proposed model allows for the analysis of multivariate dependence between variable sets with arbitrary marginal distributions. Motivated by fluorescence spectroscopy data collected from sites along the Neuse River, we also …
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Design and Evaluation of an AI-Driven Pipeline for Synthetic Tabular Data Generation
… the highest fidelity and classification utility. Gaussian Copula, however, demonstrated task-specific excellence in regression tasks where preserving explicit correlation is essential. Importantly, this research provides strong empirical evidence that a trade-off between fidelity and privacy is …
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Stochastic Ground Motion Models for Uncertainty Quantification in Earthquake Engineering
… to build joint PDFs for the GMM parameters: Gaussian copula and R-Vine copula. These investigations are critical for developing the GMM simulators. Next, this thesis develops two stochastic GM simulators as toolboxes for engineers and researchers. The first, a data-driven stochastic GM …
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Development of advanced reliability assessment models with applications in integrity management of onshore energy pipelines
… crack features is taken into account, using the Gaussian copula. At the end, the sensitivity of both the stochastic growth model and pipe segment reliability to different dependence scenarios is investigated. All the aforementioned proposed methodologies aim to assist pipeline operators in …