Abstract
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
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
