BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20230207T142037Z
UID:https://www.fhi.mpg.de/events/27097/72770
DTSTART:20210121T131500Z
CLASS:PUBLIC
CREATED:20210120T113854Z
DESCRIPTION: The goal of statistical inference is to draw conclusions about
properties of a population given a finite *observed sample*. This ty
pically proceeds by first specifying a parametric statistical model (that
identifies a likelihood function) for the data generating process which is
indexed by parameters that need to be calibrated (estimated). There is al
ways a trade-off between model simplicity / inferencial effort / predictio
n power.\, Speaker: Prof. Antonietta Mira
LAST-MODIFIED:20210615T071709Z
LOCATION:Join the webinar: https://us02web.zoom.us/j/87487369698?pwd=TnNaQm
hoOUFxMXY5QUU0R1I0Z2xCdz09\, Room: Webinar ID: 874 8736 9698 I Password: N
OMAD
ORGANIZER:NOMAD Laboratory
SUMMARY: Introduction to Approximate Bayesian Computation
URL:https://www.fhi.mpg.de/events/27097/72770
END:VEVENT
END:VCALENDAR