BEGIN:VCALENDAR
PRODID: University of Exeter
VERSION:2.0
BEGIN:VTIMEZONE
TZID:Europe/London
X-LIC-LOCATION:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:20180510T143000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:20180510T143000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
END:STANDARD
END:VTIMEZONE
METHOD:PUBLISH
BEGIN:VEVENT
SUMMARY; CHARSET=UTF-8 :Statistical science seminar: Fast computation for latent Gaussian models with a multivariate link function
UID:exeter_event_8255
URL:http://www.exeter.ac.uk/events/details/?event=8255
DTSTART;VALUE=DATE:20180510T143000
DTEND;VALUE=DATE:20180510T153000
X-MICROSOFT-CDO-ALLDAYEVENT:FALSE
ORGANIZER: MAILTO:
ATTACH: http://www.exeter.ac.uk/events/details/?event=8255
DTSTAMP:20180508T122736
LOCATION:Harrison
DESCRIPTION; CHARSET=UTF-8 :Latent Gaussian models (LGMs) form a frequently used class within Bayesian hierarchical models. This class is such that the density of the observed data conditioned on the latent parameters can be any parametric density, and the prior density of the latent parameters is Gaussian. http://www.exeter.ac.uk/events/details/?event=8255
SEQUENCE:0
PRIORITY:5
CLASS:
STATUS:CONFIRMED
TRANSP:TRANSPARENT
X-MICROSOFT-CDO-IMPORTANCE:1
X-Microsoft-CDO-BUSYSTATUS:FREE
X-MICROSOFT-CDO-INSTTYPE:0
X-Microsoft-CDO-INTENDEDSTATUS:FREE
END:VEVENT
END:VCALENDAR