Date of Award
Spring 4-25-2011
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Yichuan Zhao
Abstract
U-statistics generalizes the concept of mean of independent identically distributed (i.i.d.) random variables and is widely utilized in many estimating and testing problems. The standard empirical likelihood (EL) for U-statistics is computationally expensive because of its onlinear constraint. The jackknife empirical likelihood method largely relieves computation burden by circumventing the construction of the nonlinear constraint. In this thesis, we adopt a new jackknife empirical likelihood method to make inference for the general volume under the ROC surface (VUS), which is one typical kind of U-statistics. Monte Carlo simulations are conducted to show that the EL confidence intervals perform well in terms of the coverage probability and average length for various sample sizes.
DOI
https://doi.org/10.57709/1953322
Recommended Citation
Ma, Zhengbo, "A New Jackknife Empirical Likelihood Method for U-Statistics." Thesis, Georgia State University, 2011.
doi: https://doi.org/10.57709/1953322