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X-WR-CALNAME;VALUE=TEXT:HSPHBiostat: Neil Shephard
PRODID:-//Harvard events data//EN
BEGIN:VEVENT
UID:event_1122445_0
SUMMARY:HSPHBiostat: Neil Shephard
DESCRIPTION:<p>	<strong>Title</strong>: <a data-url="http://www.hsph.harvard.edu/biostats/events/colloq/" href="http://www.hsph.harvard.edu/biostats/events/colloq/">Moment Conditions and Bayesian Nonparametrics</a><br><br><strong>Abstract</strong>: Models phrased though moment conditions are central to much of modern inference. Here these moment conditions are embedded within a nonparametric Bayesian setup. Handling such a model is not probabilistically straightforward as the posterior has support on a manifold. We solve the relevant issues, building new probability and computational tools using Hausdorff measures to analyze them on real and simulated data. These new methods can be applied widely, including providing Bayesian analysis of quasi-likelihoods, linear and nonlinear regression, missing data and hierarchical models.</p>
LOCATION:HSPH Building II, Room 426
STATUS:CONFIRMED
DTSTART:20160128T173000Z
DTEND:20160128T190000Z
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