pald: Partitioned Local Depth for Community Structure in Data
Implementation of the Partitioned Local Depth (PaLD)
approach which provides a measure of local depth and the cohesion of a point
to another which (together with a universal threshold for distinguishing
strong and weak ties) may be used to reveal local and global structure in
data, based on methods described in Berenhaut, Moore, and Melvin (2022)
<doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional
assumptions, iterative procedures nor optimization criteria are employed.
This package includes functions for computing local depths and cohesion as
well as flexible functions for plotting community networks and displays of
cohesion against distance.
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[aut],
Kenneth Berenhaut [aut],
Lucy D'Agostino McGowan