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 39 for “"Mixture Modeling"”.
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Mixture Modeling for Multivariate Observations
… especially for multivariate observations. Mixtures, particularly nonparametric and semiparametric mixtures, have the potential to outperform the kernel-based methods, as has been shown in previous research in the univariate case. It is the main goal of this research to extend the …
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Molecular Code Division Multiple Access: Gaussian Mixture Modeling
… molecular signal is modeled as a Gaussian mixture distribution when the MC system undergoes Brownian noise and inter-symbol interference (ISI). This novel approach demonstrates a suitable modeling for diffusion-based MC system. Using the proposed Gaussian mixture model, a simple receiver is …
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Advances in mixture modeling and model based clustering
… model-based which relies on the idea of finite mixture models. This dissertations will propose new advances in clustering area mostly related to model-based clustering and its extension to the K-means algorithm. This report has five chapters. The first chapter is a literature review on recent …
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Nonparametric Bayesian Dictionary Learning and Count and Mixture Modeling
… to conventional approaches of statistical modeling. Bayesian nonparametrics constitute a promising research direction, in that such techniques can fit the data with a model that can grow with complexity to match the data. In this dissertation we consider nonparametric Bayesian modeling with …
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Large-margin Gaussian mixture modeling for automatic speech recognition
… and compares the performance of the proposed modeling scheme with existing discriminative methods such as minimum classification error (MCE) training. Experiments are performed on a standard phonetic classification task and a large vocabulary speech recognition (LVCSR) task. In the phonetic …
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Application of Hidden Markov Model in Finite Mixture Modeling of High-Dimensional Data
Finite mixture models (FMMs) are widely used in practice and are famous for modeling heterogeneous data in a convenient and effective way. Owing to their flexibility, finitemixtures have since been applied to a wide range of problems in diverse fields, includingimage analysis, medicine, …
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Bayesian Expectation-Maximization-Maximization: a latent-mixture-modeling-based Bayesian algorithm for the three-parameter logistic model
The current study proposes a Bayesian Expectation-Maximization-Maximization (Bayesian EMM, or BEMM), which is an alternative feasible Bayesian algorithm for the three-parameter logistic model (3PLM). The Bayesian EMM takes full advantage of both the EMM and the Bayesian approach. The BEMM not only …
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From expectation-3-maximization to bayesian expectation-3-maximization: A latent mixture modeling-based bayesian algorithm for the 4-parameter logistic model
… researcher reformulated the 4PLM from a latent mixture modeling view and developed the Expectation-Maximization-Maximization-Maximization (EMMM) method. Combining the EMMM with the Bayesian approach, allowed the Bayesian Expectation-Maximization-Maximization-Maximization (BEMMM) algorithm to be …
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Impact of Not Fully Addressing Cross-Classified Multilevel Structure in Testing Measurement Invariance and Conducting Multilevel Mixture Modeling within Structural Equation Modeling Framework
… settings under the structural equation modeling (SEM) framework. Study 1 evaluated the performance of conventional multilevel confirmatory factor analysis (MCFA) which assumes hierarchical multilevel data in testing measurement invariance, especially when the noninvariance exists at the …
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Identifying vaping hazards through the evaluation of exposure methods and cell culture models for e-liquid mixtures.
… for hazard identification of e-liquid binary mixtures using lung cell models. This work aims to address three critical areas: (1) utilize previously established mathematical mixture modeling for chemical interaction analysis of binary mixtures, (2) collect the condensates of heated vaping …
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The impact of early social factors on trajectories of internalizing behavior problems within maltreated foster care youth
… This study used contemporary growth mixture modeling to assess symptom trajectories of 322 youth from the Consortium for Longitudinal Studies of Child Abuse and Neglect Southwest site placed in foster care due to maltreatment. Internalizing symptom trajectories were assessed using …
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Multiple-Species Models for True Abundances Allowing for Heterogeneity of Capture Between and Within Species
… In this paper, we explore the use of finite mixture modeling to quantify species' true abundances within a population while allowing for unknown differences in the individuals' capture probabilities. This modeling also allows us to develop diversity and evenness measures based on true …
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Differential Effects of Individual Factors on the Developmental Pathways of Depression
This study used growth mixture modeling to investigate the developmental pathways of depressive symptoms across adolescence and emerging adulthood (ages 12-25 years) using a nationally representative sample (N = 20,394). Four unique non-linear trajectories were found: low-decreasing (normative), …
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Biopsychosocial Models of the Development of Childhood Disruptive Behaviors
… CP, but not vice versa. Second, I apply growth mixture modeling to identify comorbid HAP-CP developmental trajectories, as well as their uniquely associated risk factors. Finally, I attempt to replicate a well-known candidate gene by environment interaction as a predictor of CP. Altogether, …
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When Should Model Updates Propagate?
… metric grounded in Gaussian mixture modeling (GMM) of embedding distributions, capturing deeper representational shifts. Our proposed approach precisely distinguishes when deletions require downstream retraining, achieving high predictive accuracy and recall without directly …
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Does Social Competence in Preschoolers Predict Psychopathology Symptoms in Childhood and Adolescence?
… Two to four classes were identified using Growth Mixture Modeling for parent- and teacher-reported internalizing and externalizing trajectories. Generally, children who had worse preschool social competence were more likely to be in the various moderate and high psychopathology symptom trajectory …
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A Longitudinal Approach to Understanding Individual Differences Affecting the Drinking Behavior Change Process
… a short outpatient intervention. Using a growth mixture modeling (GMM) analysis, the goal was to identify different outcome drinking trajectories and examine the relationship between problem severity levels, treatment modality (i.e. individual versus group format), and goal choice (i.e. low-risk …
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An examination of psychopathy, promiscuity, and other risky sexual behavior over time
… youth antisocial behavior trajectories, growth mixture modeling techniques were employed based on age of onset and past promiscuous sexual behavior to identify patterns of promiscuity over time. However, age of sexual debut did not discriminate different patterns of promiscuous sexual behavior …
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Fear Conditioning as an Intermediate Phenotype: An RDoC Inspired Methodological Analysis
… and assume homogeneity within groups. Growth Mixture Modeling (GMM) methods such as Latent Class Growth Analysis (LCGA) may be uniquely suited for examining fear learning phenotypes. However, just three extant studies have applied GMM to fear learning and only one did so in a human population. …
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Heterogenous Trajectories Of Depressive Symptoms From Adolescence To Young Adulthood: Non-Cognitive Risk Factors And Labor Market Outcomes
… impactful labor market outcomes. Latent growth mixture modeling (GMM) was used to assess and classify depressive symptom change trajectories using four occasions of measurement from 1994 to 2008. The study used the public-use dataset from the National Study of Adolescent to Adult Health (Add …
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