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Fall 2011
Functional data analysis (FDA) is a fast-growing area in statistics with the aim of estimating a set of related functions or curves rather than focusing on a single entity, like estimating a point, as in classical statistics. FDA has a wide range of applications in different fields such as...
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Fall 2017
In this thesis, we study the partial quantile regression methods in functional data analysis. In the first part, we propose a prediction procedure for the functional linear quantile regression model by using partial quantile covariance techniques and develop a simple partial quantile regression...
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Statistical Learning and Inference For Functional Predictor Models via Reproducing Kernel Hilbert Space
DownloadFall 2024
Functional regression is a cornerstone for understanding complex relationships where predictors or responses (or both) are functions. A particularly powerful framework within this domain is the Reproducing Kernel Hilbert Space (RKHS), which facilitates the handling of infinite-dimensional data...