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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A versatile test for clustering and a proximity analysis of neurons
1Department of Preventive Medicine, School of Medicine, State University of New York, Stony Brook.
Methods of Information in Medicine
|October 1, 1991
Abstract:
A test for nonrandom patterns in populations of "cells" of binary attributes is formulated for applications in settings where it is impossible or impractical to completely specify the adjacency matrix, as in circumstances involving enormous numbers of cells and/or censored data. Applications are made to problems concerning spatial distributions of specially labeled cells in nervous system research.

