Ann Lee: "Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage"

Joint ISSI/STAMPS webinar, June 16, 2022

Speaker: Ann Lee (Carnegie Mellon University, Department of Statistics and Data Science)

Title: "Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage "
Abstract and bio: https://www.stat.cmu.edu/stamps/webin...

Organized by the STAtistical Methods for the Physical Sciences (STAMPS) research group at Carnegie Mellon University, this webinar series features colloquia-style talks for a broad audience of statisticians, data scientists and domain scientists interested in statistical challenges across astronomy, particle physics, climatology, environmental science, and other related fields.

The STAMPS research group at the Department of Statistics and Data Science at Carnegie Mellon University brings together statisticians, data scientists and physical scientists to work on statistical challenges arising in data analysis in the physical sciences. More information on STAMPS and the webinar series can be found at: http://stat.cmu.edu/stamps/