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DTSTART;TZID="Pacific Time (US & Canada)":20251031T132000
DTEND;TZID="Pacific Time (US & Canada)":20251031T143000
SUMMARY:8th Annual Post-Long Colloquium: Dr. Nicole Lazar
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DESCRIPTION:Jackknife After Bootstrap: Detecting Influential Actors in a Network\n\nAbstract: Social network analysis is a popular area of modern science. With the prevalence of larger networks and complex dependence structures, it is increasingly important to identify actors that influence the network structure by controlling the flow of information. Especially in these large networks, however, it is not practical to inspect all actors and characterize their exact influence on the entire network. Thus, a method is needed to identify influential actors so they can be flagged for further investigation. A common family of approaches is to rank actors (nodes) from most to least influential according to some network statistic such as centrality. Alternatively, one can borrow ideas prevalent in the regression literature and focus on case-deletion metrics. In this talk I describe how to use jackknife after bootstrap to detect influential nodes in a network.\n\nHere, "influence" is taken to mean nodes whose removal alters in a meaningful way the flow of information through the network.\n\nThis is joint work with Olivia Beck\n\nSpeaker Biography: Dr. Nicole Lazar is the Department Head and Professor of Statistics at Penn State. Dr. Lazar received her PhD in Statistics from the University of Chicago in 1996. She received her MS in Statistics from Stanford University in 1993, and a BA in Psychology and Statistics (highest honors) from Tel Aviv University in 1988. Her research interests include the foundations of statistical inference and the analysis of functional neuroimaging data. In particular, she has worked on fundamental inferential topics such as model selection, multiple testing problems, and likelihood theory, specifically in the context of modern large-scale data analysis problems. She has done pioneering work on the statistical analysis of cognitive neuroscience data, with a focus on functional magnetic resonance imaging (fMRI). Most recently, Lazar has been involved in the application of topological data analysis methods to scientific questions of interest in psychology and climatology. These techniques are at the interface of statistics, mathematics, and computer science, and exemplify her cross-disciplinary approach to research. A more complete biography and list of her history can be found on her faculty page.\n\nThe Calvin and Jean Long Distinguished Lecture in Mathematics\n\nAn endowed fund that brings internationally renowned mathematics scholars to the WSU campus to discuss research and current topics. A public lecture geared toward community members and members without a deep mathematical background is paired with a more in-depth colloquium with faculty and students.\n\nThe lecture honors Calvin Long, professor emeritus (1956–92) and former department chair (1970–78) and his wife, Jean.\n\n 
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