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 251 for “"GMM"”.
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Structural changes and financial frictions in the monetary transmission mechanism : GMM, VAR and Bayesian DSGE approaches
… stability. The empirical investigation employs a GMM, VAR and estimates Bayesian DSGE models for the UK data from 1955 to 2014. The GMM simulation analysis confirmed that the UK monetary policy is more of a forward-looking Taylor type and a hybrid Taylor-McCallum MP rules RFs with a mixture of …
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A Minimax Approach for Learning Gaussian Mixtures
… benchmarks including Gaussian mixture models (GMMs). In this thesis, we propose Generative Adversarial Training for Gaussian Mixture Models (GATGMM), a minimax GAN framework for learning GMMs. Motivated by optimal transport theory, we design the zero-sum game in GAT-GMM using a random linear …
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Comparison of data-driven analysis methods for identification of functional connectivity in fMRI
… version of clustering, Gaussian mixture model (GMM), and their relations. We provide a detailed empirical comparison of ICA and clustering based on GMM. We introduce a component-wise matching and comparison scheme of resulting ICA and GMM components based on their correlations. We apply this …
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A New Breast Cancer Image Classifier Using Gaussian Mixture Model Based on Histogram and Enhanced Roughness Index
… a new method based on Gaussian Mixture Model (GMM) to perform the breast tumor classification into two different classes (benign class and malignant class) was proposed. Also a new Enhance Roughness Index (ERI) was developed. In the meanwhile, the two different factors (intensity and …
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Improving Computation for Hierarchical Bayesian Spatial Gaussian Mixture Models with Application to the Analysis of THz image of Breast Tumor
… with an overview of Gaussian mixture models (GMMs). However, because in the GMM framework the observations are assumed to be independent, GMMs are less effective when the mixture data exhibits spatial autocorrelation. To improve the performance of GMMs on spatially-correlated mixture data, …
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General method of moments bias and specification tests for quantile regression
… with fixed effects. Estimating the model with GMM is consistent but suffers from small sample bias. We apply Helmert's transformation to the model, assume that error terms and nuisance parameters are homoskedastic and independent across observations and of one another, and utilize the GMM bias …
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Sustainable firm performance of green supply chain management practice at petrochemical industry
… firm performance by having Green Marketing Mix (GMM) as mediator as well as external supply chain integration as moderator on the mediator (GMM) and developing the best model of the GSCM to be implemented in the local industry. The quantitative method involved a survey of 58 respondents among …
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Fiscal Competition Among Jurisdictions: Evidence and Methodology
The proposed GMM versions of the Wald, the Likelihood ratio and the Lagrange multiplier test statistics for spatial lag dependence are based on the GMM estimator suggested by Kelejian and Robinson (1993), and on the work of Newey and West (1987). The tests are asymptotically distributed as …
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Data assimilation with Gaussian mixture models using the dynamically orthogonal field equations
… classical assimilation schemes, we introduce the GMM-DO filter: Data Assimilation with Gaussian mixture models using the Dynamically Orthogonal field equations. We combine the use of Gaussian mixture models, the EM algorithm and the Bayesian Information Criterion to accurately approximate …
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Improving the general measurement methodology
… called the "General Measurement Methodology (GMM)." The GMM as well as its variations have been used in organizations to design a measurement effort to support performance improvement. It has evolved over a number of years and is currently being researched at the International Productivity …
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Adaptive Stochastic Reduced-Order Modeling for Autonomous Ocean Platforms
… Model - Dynamically Orthogonal equations (GMM-DO) filter. The autonomous platforms can then perform principled Bayesian data assimilation onboard and learn from the limited and gappy ocean observation data and improve onboard estimates. We extend the DMD with the GMM-DO filter further by …
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Prediction of Naso-labial Morphology from Dental Pattern Assessments
… three methods: morphological, cephalometric and GMM. This study tests a hypothesis that the skeletal and dental pattern in antero-posterior and vertical dimensions and the upper and the lower incisor inclinations can predict the morphology of the soft tissue of the lips. This hypothesis was …
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Sostenibilidad corporativa y desempeño financiero: cómo el desempeño ASG determina el éxito corporativo en Latam
… que cotizan en bolsa. Utilizando un modelo GMM dinámico en sistemas, se abordan problemas de endogeneidad, heterocedasticidad y autocorrelación, garantizando estimaciones más robustas que las metodologías tradicionales. Los resultados evidencian que los pilares Ambiental (A) y Social (S) …
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Reduced order modeling for stochastic prediction and data assimilation onboard autonomous platforms at sea
… the second part, we combine DMD methods with the GMM-DO filter to produce DMD forecasts with Bayesian data assimilation that can quickly and efficiently be computed onboard an autonomous platform. We compare the accuracy of our results to traditional DMD forecasts and DMD with Ensemble Kalman …
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Preliminary Study of Highway Pavement and Materials
… (BSG), and maximum specific gravity of asphalt (Gmm) on fatigue cracking. Including 72 sections from different locations covering mix designs, pavement age between 20 and 30 years, and two U.S. climate zones, the investigation included a multiple linear regression, and the random forest (RF) …
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Reduced Order Modeling for Stochastic Prediction and Data Assimilation Onboard Autonomous Platforms At Sea
… the second part, we combine DMD methods with the GMM-DO filter to produce DMD forecasts with Bayesian data assimilation that can quickly and efficiently be computed onboard an autonomous platform. We compare the accuracy of our results to traditional DMD forecasts and DMD with Ensemble Kalman …
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Fear Conditioning as an Intermediate Phenotype: An RDoC Inspired Methodological Analysis
… 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. Thus, the degree …
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Essays in Financial Development and Income Inequality
… based on Generalized Method of Moments (GMM) method using a Chinese provincial dataset between 1998 and 2014. The empirical findings support the notion that well-developed financial markets increase income inequality in China. After adding a year dummy for 2001 to examine the impact of …
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Applications of missing feature theory to speaker recognition
… theory for improving Gaussian mixture model (GMM)-based speaker verification under this mismatch condition. Experiments are performed using a speech corpus consisting of "clean" training speech and "dirty" test speech equal to the clean speech corrupted by additive Gaussian noise. Channel …
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