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:20190331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20191027T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20190311T140000
DTEND;TZID=Europe/Paris:20190311T151500
DTSTAMP:20260713T110454
CREATED:20190117T101916Z
LAST-MODIFIED:20190117T101916Z
UID:12182-1552312800-1552317300@crest.science
SUMMARY:Ismaël CASTILLO (Sorbonne Université) - "On frequentist false discovery rate of Bayesian multiple testing procédures"
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 11 th of March 2019\nPlace: Room 3001\nIsmaël CASTILLO (Sorbonne Université) – “On frequentist false discovery rate of Bayesian multiple testing procédures” \nAbstract: In many high dimensional statistical settings\, a central task is to identify active variables among a large number of candidates. For the practitioner\, a key concern is not to make too many `false positives’\, which correspond to declaring as active an inactive variable. Given a multiple testing procedure\, a typical aim is then to control its false discovery rate (FDR)\, that is the average number of false positives. \nIn this talk\, I will consider this question for a popular Bayesian procedure\, namely the posterior distribution arising from a spike-and-slab prior\, where the sparsity parameter is calibrated by an empirical Bayes approach\, in the canonical sparse sequence model. I will introduce some commonly used Bayesian Multiple Testing procedures (BMTs) based on posterior distributions. We then ask whether such procedures control the FDR at a given target level\, for any possible true sparse signal. That is\, we consider the question of whether BMTs give a uniform control over any sparse vector of the pointwise (i.e. frequentist) false discovery rate. \nWe find that the answer is positive for natural BMTs based on empirical spike-and-slab posterior distributions\, although some of those can be slightly `conservative’. We also demonstrate that certain BMTs are not too conservative\, in the sense that they achieve a sharp FDR control at the desired target level when non-zero coordinates of the sparse signal are suitably large\, while controlling the FDR up to a constant of the target level uniformly over arbitrary sparse signals.\nThis is joint work with Étienne Roquain (Sorbonne Université).\nOrganizers:\nCristina BUTUCEA\, Alexandre TSYBAKOV\, Julie JOSSE\, Eric MOULINES\, Mathieu ROSENBAUM\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/jamal-najim-cnrs-upem-tba-2-2-3-5-2-2-2-2-2-2-3-2-2-2-2/
CATEGORIES:Statistics
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR