BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Martin Voigt Vejling (Aalborg University) DTSTART:20241121T100000Z DTEND:20241121T110000Z DTSTAMP:20260422T155052Z UID:gbgstats/74 DESCRIPTION:Title: Conformal multiple Monte Carlo testing with a view to spatial statistics \nby Martin Voigt Vejling (Aalborg University) as part of Gothenburg s tatistics seminar\n\nLecture held in MVL14.\n\nAbstract\nMonte Carlo tests are popular for their convenience\, as they allow the computation of vali d p-values even when test statistics with known and tractable distribution s are unavailable. When performing multiple Monte Carlo tests\, it is esse ntial to adjust the testing procedure to maintain control of the type I er ror\, and some of such techniques pose requirements on the joint distribut ion of the p-values\, for instance independence. A straightforward approac h to get independent p-values\, is to compute the p-values for each hypoth esis in parallel\, however\, this imposes a substantial computational burd en. We highlight in this work that the problem of testing multiple data sa mples against the same null hypothesis is an instance of conformal outlier detection. Leveraging this insight enables a more efficient multiple Mont e Carlo testing procedure\, avoiding excessive simulations while still ens uring exact control over the false discovery rate. Through numerical exper iments on point patterns we investigate the performance of this proposed c onformal multiple Monte Carlo testing (CMMCTest) procedure.\n LOCATION:https://researchseminars.org/talk/gbgstats/74/ END:VEVENT END:VCALENDAR