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 7 of 7 for “"Latent Space Model"”.
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Statistical methods for indirectly observed network data
… Yet, despite an abundance of sophisticated models, social network research has yet to realize its full potential, in part because of the difficulty of collecting social network data. In many cases, particularly in the social sciences, collecting complete network data is logistically and …
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Estimation and Inference for Network Data
… question we analyze concerns how to understand latent structure in networks. Specifically, we propose a method that estimates the latent type, dimension, and curvature of the latent space model. The second problem we consider concerns network data collection. Collecting full network data is …
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Advanced Robust Statistical Learning Methods with Application in Healthcare and Manufacturing
… sample size, I developed a flow-based generative model termed Disentangled Adversarial Flow or DAF for short, which leverages large-scale multi-source datasets to improve prediction accuracy in neuroimaging studies with smaller sample sizes. A bidirectional-generative architecture and a …
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Statistical inference for complex networks
… of statistical methods have been proposed for modeling such relational data, identifying community structures, hypothesis testing, and model selection. The majority of these methods dealt with the case where only one network observation is available. However, as the data collection ability …
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Statistical models and inference for dynamic networks
… networks. A general framework is developed for modeling dynamic networks via a latent space approach. Using a latent space approach to model such networks allows the researcher to model both the local and global structure of the network, inherently accounts for transitivity, and yields rich and …
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Statistical inference in complex networks: community detection, change-point detection, link prediction, and two-sample testing
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01
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Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01