Abstract Graphs are building blocks for many statistical techniques. Recent work has addressed graph construction to improve the end result of the associated statistical analysis. In this article, we propose a new method to efficiently construct a nearest neighbor graph where the vertices are variables. Our primary application is covariance or concentration matrix estimation, where graphs are constructed to examine relationships between variables and to uncover data set structure. We demonstrat.
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