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 20 of 2460 for “"Latent"”.
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Bayesian Latent Class Models
The latent class model (LCM) is a statistical method that introduces a set of latent categorical variables. The main advantage of LCM is that conditional on latent variables, the manifest variables are mutually independent of each other. In some scenarios, the LCM makes the modeling or computation …
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Latent Clustered Causal Models
… directed graphical models in the presence of latent variables. We define latent clustered causal models as a particular restriction on directed graphical models with latent variables and corresponding clusters of observed nodes, characterized by edges between only observed and latent …
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Domain latent class models, equivalent set latent class models, and kernel factor analysis
This Dissertation was approved for publication on 2024-11-26 at 08:35.
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Latent factor modelling of disability
… uses survey data and involves the application of latent factor structural equation methods to the study of the economics of disability and disability policy in later life, a topic which is currently very high on the policy agenda. It comprises four studies. The first chapter investigates the …
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Latent heat storage in concrete
… the concrete. These PCM's absorb or release the latent heat of fusion at a selected temperature and thereby greatly enhance the heat storage capacity of the impregnated concrete over a small temperature range. Modification of the concretes were performed to enhance their compatibility with the …
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Identifiability for latent class models
Despite the fact that latent class models have been widely applied and appeared to perform well in various applications, it is well known that inference for latent class models is challenging due to the potential nonidentifiability of the underlying model parameters. In other words, multiple or …
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Matrix estimation with latent permutations
… matrix with rows and columns shuffled by latent permutations, given noisy and incomplete observations of its entries. This problem is at the intersection of shape constrained estimation which has a long history in statistics, and latent permutation learning which has driven a recent surge …
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Adolescent Risk Behaviors: Examining Latent Classes And Latent Transition Statuses In A Longitudinal Bahamian Sample
… that co-occur among different subsets of youth. Latent class analysis and latent transition analysis revealed four distinct profiles of risk behavior involvement. Latent classes of grade 12 behaviors included a low risk class, a high risk class and two moderate risk behaviors classes. The …
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Mixed Mode Latent Class Clustering: An Examination of Fit Index Performance for Identifying Latent Classes
… used by applied researchers interested in latent class clustering (LCC) or finite mixture models. The goal of LCC is to classify subjects from a large heterogeneous set of cases into homogeneous subgroups when the number of subgroups is unknown a priori. Despite the advantages of LCC over …
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Capturing Latent Abilities and Latent Capacities of Professional Golfers Using Nonlinear Mixed Effects Growth Modeling
… and innovative approach to measuring the latent athletic abilities and capacities of professional golfers. I used nonlinear mixed effects growth modeling (e.g., Dynamic Measurement Modeling) to measure professional golfers’ ability levels and capacities for improvement. I accomplished this …
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Identifying latent profiles of psilocybin use
… This research uses mixture modeling to identify latent profiles of psilocybin use in a large population of adults endorsing lifetime psilocybin. Data for this project was sourced anonymously from subreddit community sites. I found three profiles indicated by frequency and quantity of psilocybin …
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Latent Space Modeling for Environmental Systems
… thesis presents a comprehensive exploration of latent space modeling techniques developed to improve the accuracy and efficiency of environmental and hydrological predictions. The crux of this research lies in developing and applying machine learning models that can effectively integrate and …
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Serotonin and Norepinephrine in Latent Inhibition.
… affected subjects* performance in the latent inhibition paradigm. This evidence was correlated with earlier work which showed norepinephrine depletions attenuating performance in blocking, whereas serotonin-depleted rats behaved like normals in the paradigm. Thus, different …
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Interpretability of Neural Networks Latent Representations
… output of these models, leaving their internal latent representations unexplored. In this thesis, we describe how interpretability research has recently expanded its scope beyond the output of neural networks. We focus on 3 types of interpretability methods: feature importance, example-based and …
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Latent state space models for prediction
… Markov model. The new 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 …
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Modeling driving decisions with latent plans
… specific plan. The plan is however unobserved or latent and only the manifestations of the plan through actions are observed. Examples include selection of a target lane before execution of the lane change, choice of a merging tactic before execution of the merge. Change in circumstances (e.g. …
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Latent source models for nonparametric inference
… in which the data appear generated from unknown "latent sources" that capture salient structure in the problem. These latent source models naturally lead to nearest-neighbor or nearest-neighbor-like inference methods similar to ones already used in practice. We derive theoretical performance …
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Latent Class Model in Transportation Study
… as to establish the statistical models for the latent structure of data. Over the past several years, the interest in latent class models has continuously increased due to their great potential in solving practical problems. In this dissertation, I developed several latent class models to …
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The Relation between Uncertainty in Latent Class Membership and Outcomes in a Latent Class Signal Detection Model
Latent class variables are often used to predict outcomes. The conventional practice is to first assign observations to one of the latent classes based on the maximum posterior probabilities. The assigned class membership is then treated as an observed variable and used in predicting the outcomes. …
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