Graphical Modeling for High Dimensional Data

Munni Begum, Jay Bagga, C. Ann Blakey
2012 Journal of Modern Applied Statistical Methods  
With advances in science and information technologies, many scientific fields are able to meet the challenges of managing and analyzing high-dimensional data. A so-called large p small n problem arises when the number of experimental units, n, is equal to or smaller than the number of features, p. A methodology based on probability and graph theory, termed graphical models, is applied to study the structure and inference of such high-dimensional data.
doi:10.22237/jmasm/1351743360 fatcat:eljmhzdac5cntcdybnvcvhderi