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Nicole Lazar, University of Georgia

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Bayesian Empirical Likelihood for Ridge and Lasso Regression
When
12 September 2019 from 3:30 PM to 4:30 PM
Where
201 Thomas Building
Contact Name
Contact Phone
8149352416
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Empirical likelihood (EL) is a nonparametric analog of standard likelihood, and inherits many of its properties.  Accordingly, Bayesian EL, which replaces the ordinary likelihood function with an empirical likelihood function, has been developed.  In this talk, I will briefly introduce empirical likelihood in both its standard and Bayesian versions.  A recent development is Bayesian EL for regularized methods such as ridge regression.  The theoretical background for Bayesian ridge and Bayesian lasso empirical likelihoods will be presented, along with discussion of computational issues.   

This is joint work with Adel Bedoui.

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