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 |
| Author: |
Subhadeep Mukhopadhyay, Kaijun Wang |
| Maintainer: |
Kaijun Wang <kaijun.wang at temple.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
LPGraph results |
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