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 6 of 6 for “"functional linear model"”.
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Sparse functional regression models: minimax rates and contamination
In functional linear regression and functional generalized linear regression models, the effect of the predictor function is usually assumed to be spread across the index space. In this dissertation we consider the sparse functional linear model and the sparse functional generalized linear models …
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On Wavelet-Based Methods for Scalar-on-Function Regression
… projects which extend 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 …
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Bayesian analysis of historical functional linear models with application to air pollution forecasting
Historical functional linear models are used to analyse the relationship between a functional response and a functional predictor whereby only the past of the predictor process can affect the current outcome. In this work, we develop a Bayesian framework for the analysis of the historical …
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Modeling Size-Resolved Particle Number Emissions From Advanced Technology And Alternative Fueled Vehicles In Real-Operating Conditions
… filters and ultra-low sulfur diesel fuel. A linear mixed model was used to control for multiple sources of variability in real-world particle measurements, and identified significant factors influencing particle number emissions. Subsequently, link-level particle number emission models were …
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Modern Methods for Variable Significance Testing
… Hilbert spaces with a focus on applications to functional data. The first main result of the chapter shows that for functional data it is impossible to construct a non-trivial test for conditional independence even when assuming that the data are jointly Gaussian. A novel regression-based test, …