Author ORCID Identifier
Date Available
7-21-2017
Year of Publication
2017
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Arts and Sciences
Department/School/Program
Statistics
Advisor
Dr. Richard Charnigo
Abstract
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. Finally, we applied our change point detection method to a glucose level data set and identified the meal consumption time for five patients.
Digital Object Identifier (DOI)
https://doi.org/10.13023/ETD.2017.312
Recommended Citation
Liu, Sisheng, "NONPARAMETRIC COMPOUND ESTIMATION, DERIVATIVE ESTIMATION, AND CHANGE POINT DETECTION" (2017). Theses and Dissertations--Statistics. 29.
https://uknowledge.uky.edu/statistics_etds/29
Included in
Applied Statistics Commons, Statistical Methodology Commons, Statistical Models Commons, Statistical Theory Commons
