BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//University of Utah Math Department//Bayesian graphical models for multivariate functional data//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Bayesian graphical models for multivariate functional data
X-WR-CALDESC:Bayesian graphical models for multivariate functional data at University of Utah Mathematics Department
X-WR-TIMEZONE:America/Denver
BEGIN:VEVENT
UID:20120126T160000-hongxiao-zhu@math.utah.edu
DTSTART;TZID=America/Denver:20120126T160000
DTEND;TZID=America/Denver:20120126T170000
DTSTAMP:20260922T150858Z
SUMMARY:Bayesian graphical models for multivariate functional data
DESCRIPTION:Speaker: Hongxiao Zhu\, Duke University\n\nIn a broad variety of application areas there is interest in inferring the dependence structure in multivariate functional data. For data in vector form, conditional independence relationships between variables can be inferred through allowing zeros in the precision matrix through a Gaussian …

LOCATION:JWB 335

URL:https://www.math.utah.edu/research/colloquia/2012-01-26-hongxiao-zhu/
END:VEVENT
END:VCALENDAR