BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CREST - ECPv5.1.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CREST
X-ORIGINAL-URL:https://crest.science
X-WR-CALDESC:Events for CREST
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20180325T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20181028T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20180504T140000
DTEND;TZID=Europe/Paris:20180504T153000
DTSTAMP:20260715T023218
CREATED:20180419T132954Z
LAST-MODIFIED:20180419T132954Z
UID:12044-1525442400-1525447800@crest.science
SUMMARY:Quentin F. GRONAU (University of Amsterdam) - "Bayesian Model Comparison for Hierarchical Multinomial Processing Tree Models using Warp-III Bridge Sampling"
DESCRIPTION:\nThe BiP Seminar\nTime: 2:00 pm – 3:30 pm\nDate: 4th of May 2018\nPlace: Room 3001.\nQuentin F. GRONAU (University of Amsterdam) “Bayesian Model Comparison for Hierarchical Multinomial Processing Tree Models using Warp-III Bridge Sampling “ \nAbstract: \nMultinomial processing trees (MPTs) are substantively motivated stochastic models for the analysis of categorical data. MPTs are popular in various areas of psychology and have been applied\, for instance\, in research on memory\, perception\, logical reasoning\, and attitudes. MPTs allow researchers to test theories about cognitive architecture by formalizing qualitatively different cognitive processes that underlie performance in an experimental paradigm. In typical applications\, researchers compare several MPTs\, each equipped with many parameters\, especially when the models are implemented in a hierarchical framework. A Bayesian solution is to compute posterior model probabilities and Bayes factors. Both quantities\, however\, rely on the marginal likelihood\, a high-dimensional integral that cannot be evaluated analytically. Here\, we demonstrate how Warp-III bridge sampling can be used to compute the marginal likelihood for hierarchical MPTs. We illustrate the procedure with two published data sets. \n \nOrganizers:\nNicolas CHOPIN – Robin RYDER\nSponsors:\nCREST\n \n\n
URL:https://crest.science/event/jamal-najim-cnrs-upem-tba-2-2-3-4/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR