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).


Reference manual

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2.1 by Kaijun Wang, 2 years ago

Browse source code at

Authors: Subhadeep Mukhopadhyay , Kaijun Wang

Documentation:   PDF Manual  

GPL-2 license

Depends on stats, car, PMA

Imported by LPsmooth.

Depended on by LPKsample.

See at CRAN