Network Inference from Grouped Data
dc.contributor.advisor | Zhao, Yungpen | |
dc.contributor.author | Weko, Charles William | |
dc.creator | Weko, Charles William | |
dc.date.accessioned | 2015-07-29T18:42:49Z | |
dc.date.available | 2015-07-29T18:42:49Z | |
dc.date.issued | 2015 | |
dc.description.abstract | In the past two decades, the interest in network analysis has expanded rapidly. Most network analysis methods start from observed network topology. However, network structure is not directly observed in many fields, especially in social sciences. Thus, a methodology for inferring implicit network structure is required to effectively apply network analysis. One area of research involves the inference of network structure from \textit{grouped data}. Grouped data records the manner in which a population forms subsets or smaller groups. | |
dc.format.extent | 106 pages | |
dc.identifier.uri | https://hdl.handle.net/1920/9696 | |
dc.identifier.uri | https://doi.org/10.13021/MARS/4499 | |
dc.language.iso | en | |
dc.rights | Copyright 2015 Charles William Weko | |
dc.subject | Statistics | |
dc.subject | Affiliation network | |
dc.subject | Dream of the Red Chamber | |
dc.subject | L1 regularization | |
dc.title | Network Inference from Grouped Data | |
dc.type | Dissertation | |
thesis.degree.discipline | Statistical Science | |
thesis.degree.grantor | George Mason University | |
thesis.degree.level | Doctoral |
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