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VERSION:2.0
PRODID:-//EventXplore//EN
CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:7da995f6-0376-4b5f-8a2b-0d309eaaeae3@eventxplore
DTSTAMP:20260928T195837Z
DTSTART:20261023T180000Z
DTEND:20261023T190000Z
SUMMARY:Statistics Seminar Series: Efficient and Stable Box-Cox Regression for High-Dimensional Data Analysis
DESCRIPTION:Please join the Statistics Department for a talk titled\, 'Efficient and Stable Box-Cox Regression for High-Dimensional Data Analysis' featuring Prof. Hui Zou\, from Johns Hopkins University. The Box-Cox transformation paper ranks among the five most-cited articles in the Journal of the Royal Statistical Society\, Series B. Bickel and Doksum (1981) revisited this classical model through analysis of the profile likelihood estimator and concluded that "the performance of all Box-Cox type procedures is unstable." We argue\, however\, that the scientific modeling philosophy of Box and Cox remains valua
LOCATION:Duques Hall
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