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Full-Text Articles in Physical Sciences and Mathematics
Nonparametric Compound Estimation, Derivative Estimation, And Change Point Detection, Sisheng Liu
Nonparametric Compound Estimation, Derivative Estimation, And Change Point Detection, Sisheng Liu
Theses and Dissertations--Statistics
Firstly, we reviewed some popular nonparameteric regression methods during the past several decades. Then we extended the compound estimation (Charnigo and Srinivasan [2011]) to adapt random design points and heteroskedasticity and proposed a modified Cp criteria for tuning parameter selection. Moreover, we developed a DCp criteria for tuning paramter selection problem in general nonparametric derivative estimation. This extends GCp criteria in Charnigo, Hall and Srinivasan [2011] with random design points and heteroskedasticity. Next, we proposed a change point detection method via compound estimation for both fixed design and random design case, the adaptation of heteroskedasticity was considered for the method. …
Developments In Nonparametric Regression Methods With Application To Raman Spectroscopy Analysis, Jing Guo
Developments In Nonparametric Regression Methods With Application To Raman Spectroscopy Analysis, Jing Guo
Theses and Dissertations--Epidemiology and Biostatistics
Raman spectroscopy has been successfully employed in the classification of breast pathologies involving basis spectra for chemical constituents of breast tissue and resulted in high sensitivity (94%) and specificity (96%) (Haka et al, 2005). Motivated by recent developments in nonparametric regression, in this work, we adapt stacking, boosting, and dynamic ensemble learning into a nonparametric regression framework with application to Raman spectroscopy analysis for breast cancer diagnosis. In Chapter 2, we apply compound estimation (Charnigo and Srinivasan, 2011) in Raman spectra analysis to classify normal, benign, and malignant breast tissue. We explore both the spectra profiles and their derivatives to …