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).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.1 |
rolling linux/jammy R-4.5 | LPGraph_2.1.tar.gz |
65.6 KiB |
2.1 |
rolling linux/noble R-4.5 | LPGraph_2.1.tar.gz |
65.5 KiB |
2.1 |
rolling source/ R- | LPGraph_2.1.tar.gz |
46.8 KiB |
2.1 |
latest linux/jammy R-4.5 | LPGraph_2.1.tar.gz |
65.6 KiB |
2.1 |
latest linux/noble R-4.5 | LPGraph_2.1.tar.gz |
65.5 KiB |
2.1 |
latest source/ R- | LPGraph_2.1.tar.gz |
46.8 KiB |
2.1 |
2026-04-26 source/ R- | LPGraph_2.1.tar.gz |
46.8 KiB |
2.1 |
2026-04-23 source/ R- | LPGraph_2.1.tar.gz |
46.8 KiB |
2.1 |
2026-04-09 windows/windows R-4.5 | LPGraph_2.1.zip |
68.2 KiB |
2.1 |
2025-04-20 source/ R- | LPGraph_2.1.tar.gz |
46.8 KiB |