Some Recent Advances in Non- and Semiparametric Bayesian Modeling with Copulas, Mixtures, and Latent Variables

Some Recent Advances in Non- and Semiparametric Bayesian Modeling with Copulas, Mixtures, and Latent Variables

<p>This thesis develops flexible non- and semiparametric Bayesian models for mixed continuous, ordered and unordered categorical data. These methods have a range of possible applications; the applications considered in this thesis are drawn primarily from the social sciences, where multivariat...

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Bibliographic Details
Main Author: Murray, Jared
Other Authors: Reiter, Jerome P
Published: 2013
Subjects:
Statistics
Bayesian methods
Bayesian Nonparametrics
Copula Modeling
Density Regression
Mixture Modeling
Multiple Imputation
Online Access:http://hdl.handle.net/10161/8253

Internet

http://hdl.handle.net/10161/8253

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