LPGraph: Nonparametric Smoothing of Laplacian Graph Spectra

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:	2.1
Depends:	R (≥ 3.5.0), stats, car, PMA
Published:	2020-01-30
DOI:	10.32614/CRAN.package.LPGraph
Author:	Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer:	Kaijun Wang <kaijun.wang at temple.edu>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	LPGraph results

Documentation:

Reference manual:

LPGraph.pdf

Downloads:

Package source:	LPGraph_2.1.tar.gz
Windows binaries:	r-devel: LPGraph_2.1.zip, r-release: LPGraph_2.1.zip, r-oldrel: LPGraph_2.1.zip
macOS binaries:	r-release (arm64): LPGraph_2.1.tgz, r-oldrel (arm64): LPGraph_2.1.tgz, r-release (x86_64): LPGraph_2.1.tgz, r-oldrel (x86_64): LPGraph_2.1.tgz
Old sources:	LPGraph archive

Reverse dependencies:

Reverse depends:	LPKsample
Reverse imports:	LPsmooth

Linking:

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