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CATEGORIES:Lecture
DESCRIPTION:From OLS to High-dimensional Linear Regression -\nLinear regres
sion is commonly used in statistical analysis\, and is one of the most impo
rtant tools we learn in an introductory statistics course. What happens whe
n we extend the setting to high-dimensional data\, that is\, data with more
variables than observations? This talk will look at issues that arise in r
egression with high-dimensional data\, how frequentists and Bayesians solve
the problem\, and my research\, a Bayesian-adjacent method that uses empir
ical priors for high-dimensional linear regression.
DTEND:20221118T014000Z
DTSTAMP:20230323T183741Z
DTSTART:20221118T004000Z
LOCATION:Eliot 314
SEQUENCE:0
SUMMARY:Statistics Job Talk: Annie Tang\, North Carolina State University
UID:tag:localist.com\,2008:EventInstance_41600363068653
URL:https://events.reed.edu/event/statistics_job_talk_annie_tang_north_caro
lina_state_university
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