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 8 of 8 for “"Mixture Regression"”.
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Robust mixture regression using mean-shift penalisation
The purpose of finite mixture regression (FMR) is to model the relationship between a response and feature variables in the presence of latent groups in the population. The different regression structures are quantified by the unique parameters of each latent group. The Gaussian mixture regression …
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Investigating the Various Ways Parental Incarceration Affects Children: An Application of Mixture Regression
… and previous incarceration are outlined. Using mixture regression, the various ways children are affected are identified. Child, family, and neighborhood characteristics are used to predict these effects. For concurrent incarceration, only 3% of the sample was unaffected (positively or …
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Robust mixtures of regression models
… contains two projects that are related to robust mixture models. In the robust project, we propose a new robust mixture of regression models (Bai et al., 2012). The existing methods for tting mixture regression models assume a normal distribution for error and then estimate the regression param- …
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Robot Learning Assembly Tasks from Human Demonstrations
… the robot with feedback in real-time. Gaussian Mixture Model and Gaussian Mixture Regression are used to encode the learned skills for the robot. Finally, The effectiveness of the approach is evaluated with practical assembly tasks by the Baxter robot. The significance of this thesis research is …
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On Wavelet-Based Methods for Scalar-on-Function Regression
… and employ wavelet-based functional linear regression. In the first project, we propose a wavelet-based approach to functional mixture regression. In our approach, the functional predictor and the unknown component-specific coefficient functions are projected onto an appropriate wavelet …
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Estimation of glottal source features from the spectral envelope of the acoustic speech signal
… A transformation method based on Gaussian mixture regression (GMR) is presented and compared to current IF methods in terms of feature similarity, reliability, and speaker discrimination capability on a large speech corpus, and potential representations of the spectral envelope of speech …
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Bayesian Adaptive Designs for Early Phase Clinical Trials
… treatment evaluation, the design uses a mixture regression model that jointly models short-term and long-term response outcomes. In addition, a data-driven latent class model is employed to adaptively combine subgroups into induced latent classes based on overall data heterogeneities, …
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High-Dimensional Functional Graphs and Inference for Unknown Heterogeneous Populations
… combines the strengths of FGMs with finite mixture of regression models (FMR) to overcome the challenges of estimating conditional dependence structures from heterogeneous functional data. This novel approach facilitates the discovery of latent patterns, proving particularly advantageous for …