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Activity Number: 566
Type: Contributed
Date/Time: Thursday, August 6, 2009 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #304363
Title: Bivariate Models with Partially Known Marginals: An Empirical Likelihood Approach with Infinitely Many Constraints
Author(s): Anton Schick*+ and Hanxiang Peng
Companies: Binghamton University and Indiana University Purdue University Indianapolis
Address: Department of Mathematical Sciences, Binghamton, NY, 13902-6000,
Keywords: Effficient Estimation ; Maximum Empirical Likelihood Estimator
Abstract:

We first look at bivariate data with known marginals and review existing methods of efficient estimation of linear functionals. Then we present a new method based on the empirical likelihood approach with infinitely many constraints. Finally we discuss extensions of the method to inference problems when the marginals are parametric. This includes confidence intervals for and efficient estimation of the parameters.

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