BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UM//UM*Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Detroit TZURL:http://tzurl.org/zoneinfo/America/Detroit X-LIC-LOCATION:America/Detroit BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240729T164045 DTSTART;TZID=America/Detroit:20240813T150000 DTEND;TZID=America/Detroit:20240813T170000 SUMMARY:Lecture / Discussion:Statistical Modelling of Spatially and Spatio-Temporally Dependent Data: Some Theoretical Results and an Application DESCRIPTION:This dissertation is concerned with data exhibiting spatial and spatio-temporal dependence. It is based on three separate research works.\n\nOne chapter is concerned with the biogeochemical Argo data in the Southern Ocean\, which aims to collect measurements of oxygen\, temperature and salinity as well as other variables at varying depths in the ocean. The biogeochemical Argo data is important to improve our understanding of vital biogeochemical processes such as the biological carbon pump and air-sea CO2 exchanges\, monitor changes such as ocean deoxygenation and acidification\, and improve estimates of the carbon budget. We introduce and estimate a functional regression model for oxygen\, temperature\, and salinity data. Our model elucidates important aspects of the joint distribution of temperature\, salinity\, and oxygen across the entire ocean depth covered by the Argo data and improves location estimates of so-called oceanographic fronts\, which are of significant scientific interest in their own right. In addition\, it enables us to use the more pervasively available temperature and salinity data to recover biogeochemical data at locations where it is not observed.\n\nAnother chapter\, motivated by the work on the Argo data\, contributes to the solution of an open problem in the spatial statistics literature. Concretely\, we study the smoothness estimation of so-called Whittle-Matérn kernels on closed Riemannian manifolds. The smoothness of Matérn kernels controls\, for example\, optimal error bounds for kriging and posterior contraction rates in Gaussian process regression. However\, it has been an open problem whether their smoothness can always be consistently estimated. On closed Riemannian manifolds\, we show that their smoothness can be consistently estimated from the maximizer(s) of the Gaussian likelihood when the underlying data stem from point evaluations of a Gaussian process and\, perhaps surprisingly\, even when the data comprise evaluations of a non-Gaussian process. Moreover\, we generalize a well-known equivalence of measures phenomenon related to Matérn kernels to the non-Gaussian case by using Kakutani's theorem.\n\nThe remaining chapter extends this work to processes observed on the vertices of graphs. Due to increased tractability of the problem is this setting\, we are able to provide more complete results. In addition\, we establish connections to processes observed on smooth domains such as Riemannian manifolds. In this way\, we believe that our results for processes on graphs provide additional insights for such cases as well. UID:123648-21851239@events.umich.edu URL:https://events.umich.edu/event/123648 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Dissertation LOCATION:West Hall - 438 CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20240828T123142 DTSTART;TZID=America/Detroit:20240813T160000 DTEND;TZID=America/Detroit:20240813T170000 SUMMARY:Careers / Jobs:AmeriCorps NCCC: A to Z Webinar DESCRIPTION:Eager for Adventure? Join us for an info session about AmeriCorps NCCC to discover how this national service opportunity offers travel across the country\, building job skills like leadership\, earning money for school\, and the chance to make a difference. \;The webinar will be interactive\, share about our program options\, walk through all the benefits\, and cover the requirements to serve. We’ll help you decide if NCCC is the right fit for you! \;Note: There are two age requirements to serve in AmeriCorps NCCC. Corps members are 18-26 and team leaders are 18 and older (no upper age limit). UID:122866-21849729@events.umich.edu URL:https://events.umich.edu/event/122866 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES: LOCATION: CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20240828T123144 DTSTART;TZID=America/Detroit:20240813T160000 DTEND;TZID=America/Detroit:20240813T170000 SUMMARY:Careers / Jobs:SMBC Information Session: Women's Colleges Edition DESCRIPTION:SMBC Information Session: Women’s Colleges EditionWe invite all sophomores\, juniors\, and seniors who are attending a Women’s College to our SMBC Information Session: Women’s Colleges Edition. We understand how the recruitment process can be overwhelming at times. This session was designed with your best interests in mind. From learning about our SMBC brand\, our businesses\, and intern and analyst programs to gaining insights into the interview process\, we are confident that you will be better prepared for your career journey.Candidates from all backgrounds and majors are invited to join!Come get to know usAt SMBC\, we are growing and transforming alongside our clients. This means we need experienced collaborators tohelp us continue on our path of globalization\, diversification\, and expansion. We are developing teams of dynamic seekers who are looking to build something great and lasting for themselves\, our clients\, and our company.We invite sophomores and juniors to meet us virtually\,4:00 p.m. to 5:00 p.m. ET\, August 14.Date: Wednesday\, August 14Time: 4:00PM to 5:00PM ETLocation: WebexMeeting Number: 2631 439 4583Meeting Password: Fall2024  UID:122941-21849821@events.umich.edu URL:https://events.umich.edu/event/122941 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES: LOCATION: CONTACT: END:VEVENT END:VCALENDAR