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TZID:America/Toronto
BEGIN:STANDARD
DTSTART:20181104T020000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
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UID:calendar.1213.field_event_date.0@uwaterloo.ca/statistics-and-actuarial-
science
DTSTAMP:20210127T105622Z
CREATED:20181015T184351Z
DESCRIPTION:Copula Gaussian graphical models for functional data\n\n\n\nWe
consider the problem of constructing statistical graphical models for func
tional data\; that is\, the observations on the vertices are random functi
ons. This types of data are common in medical applications such as EEG and
fMRI. Recently published functional graphical models rely on the assumpti
on that the random functions are Hilbert-space-valued Gaussian random elem
ents. We relax this assumption by introducing a copula Gaussian random el
ements Hilbert spaces\, leading to what we call the Functional Copula G
aussian Graphical Model (FCGGM). This model removes the marginal Gaussian
assumption but retains the simplicity of the Gaussian dependence structure
\, which is particularly attractive for large data. We develop four estima
tors\, together with their implementation algorithms\, for the FCGGM. We e
stablish the consistency and the convergence rates of one of the estimator
s under different sets of sufficient conditions with varying strengths. We
compare our FCGGM with the existing functional Gaussian graphical model b
y simulation\, under both non-Gaussian and Gaussian graphical models\, and
apply our method to an EEG data set to construct brain networks.
DTSTART;TZID=America/Toronto:20181101T160000
DTEND;TZID=America/Toronto:20181101T160000
LAST-MODIFIED:20181015T184358Z
LOCATION:M3 - Mathematics 3\n \n\n Room: 3127 \n
\n\n \n\n 200 University Avenue West \n
Waterloo\, ON\n
N2L 3G1\n \nCanada
SUMMARY:Department seminar by Dr. Bing Li\, Pennsylvania State University
URL;TYPE=URI:https://uwaterloo.ca/statistics-and-actuarial-science/events/d
epartment-seminar-dr-bing-li-pennsylvania-state-university
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