A nonparametric method to approximate Laplacian graph spectra of a network with ordered vertices. This provides a computationally efficient algorithm for obtaining an accurate and smooth estimate of the graph Laplacian basis. The approximation results can then be used for tasks like change point detection, k-sample testing, and so on. The primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).
Version: | 2.0 |
Depends: | R (≥ 2.10), stats, SDMTools, car, PMA |
Published: | 2018-05-13 |
Author: | Subhadeep Mukhopadhyay, Kaijun Wang |
Maintainer: | Kaijun Wang <kaijun.wang at temple.edu> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | LPGraph results |
Reference manual: | LPGraph.pdf |
Package source: | LPGraph_2.0.tar.gz |
Windows binaries: | r-devel: LPGraph_2.0.zip, r-release: LPGraph_2.0.zip, r-oldrel: LPGraph_2.0.zip |
OS X binaries: | r-release: LPGraph_2.0.tgz, r-oldrel: LPGraph_2.0.tgz |
Old sources: | LPGraph archive |
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