The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
304
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Statistical Computing
|
Abstract - #302364 |
Title:
|
Application of Evolutionary Algorithms in Estimation of Empirical Likelihoods
|
Author(s):
|
Ashley Askew*+
|
Companies:
|
University of Georgia
|
Address:
|
101 Cedar Street, Athens, GA, 30602,
|
Keywords:
|
Evolutionary algorithm ;
Empirical Likelihood
|
Abstract:
|
An evolutionary algorithm (EA) is a flexible global optimization routine, as well as an alternative to the conventional numerical methods based on derivatives. Empirical likelihoods (ELs) are a non-parametric formulation that utilizes the data to construct a likelihood. The estimation of ELs can pose challenges, especially when constraints must be incorporated in the likelihood. In this work, we compare the performance of a penalized EA against a numerical procedure based on Newton-Raphson in estimating various examples of ELs.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.