BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:Europe/Vienna
BEGIN:DAYLIGHT
DTSTART:20170326T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20161030T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20240914T202415Z
UID:57f7915881f68780214077@ist.ac.at
DTSTART:20170307T160000
DTEND:20170307T180000
DESCRIPTION:Speaker: Johannes Heiny\nhosted by Laszlo ErdÃ¶s\nAbstract: We
study the joint distributional convergence of the largest eigenvalues of t
he sample covariance matrix of a p-dimensional heavy-tailed time series wh
en p converges to infinity together with the sample size n. We generalize
the growth rates of p existing in the literature. Assuming a regular varia
tion condition with tail index alpha<4\, we employ a large deviations appr
oach to show that the extreme eigenvalues are essentially determined by th
e extreme order statistics from an array of iid random variables. The asym
ptotic behavior of the extreme eigenvalues is then derived routinely from
classical extreme value theory. The resulting approximations are strikingl
y simple considering the high dimension of the problem at hand.\n\nWe deve
lop a theory for the point process of the normalized eigenvalues of the sa
mple covariance matrix in the case where rows and columns of the data are
linearly dependent. Based on the weak convergence of this point process we
derive the limit laws of various functionals of the eigenvalues.\n\nThis
talk is based on a joint work with Richard Davis and Thomas Mikosch.\n
LOCATION:Seminar room Big Ground floor / Office Bldg West (I21.EG.101)\, IS
TA
ORGANIZER:jdeanton@ist.ac.at
SUMMARY:Johannes Heiny: Limit theorems for the largest eigenvalues of the s
ample covariance matrix of a heavy-tailed time series
URL:https://talks-calendar.ista.ac.at/events/298
END:VEVENT
END:VCALENDAR