Dessertation defense-Lang Zhou
Event Type:
Other
Speaker:
Lang Zhou
Event Date:
Tuesday, April 5, 2016 -
3:30pm to 5:30pm
Location:
SMLC356
Audience:
General PublicFaculty/StaffStudentsAlumni/Friends
Sponsor/s:
Stats
Event Description:
Title: Neyman Smooth-Type Goodness of Fit
Tests in Complex Surveys
Abstract: In this study, we have extended the Neyman smooth-type goodness of t tests by
Eubank (1997) from Simple Random Sample to complex surveys by incorporating
consistent estimators under the survey design, which is accomplished by a data-driven
nonparametric order selection method. Simulation results show that these proposed
methods potentially improve the statistical power while controlling the type I error
very well compared to those commonly used existing test procedures, especially for
the cases with slow-varying probabilities. We also derived the large sample properties
of the test statistics, which have been supported by our simulation studies.
Several practical examples are provided to illustrate the usage and advantages of our
proposed methods.
