casc: Covariate Assisted Spectral Clustering
In norbertbin/SpecClustPack: Spectral Clustering for Network Analysis

Covariate Assisted Spectral Clustering

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casc(adjMat, covMat, nBlocks, nPoints = 100, method = "regLaplacian",
  rowNorm = F, center = F, verbose = F, assortative = F,
  randStarts = 20)

`adjMat`	An adjacency matrix
`covMat`	A covariate matrix
`nBlocks`	The number of clusters
`nPoints`	Number of iterations to find the optimal tuning parameter.
`method`	The form of the adjacency matrix to be used.
`rowNorm`	True if row normalization should be done before running kmeans.
`center`	A boolean indicating if the covariate matrix columns should be centered.
`verbose`	A boolean indicating if casc output should include eigendecomposition.
`assortative`	A boolean indicating if the assortative version of casc should be used.
`randStarts`	Number of random restarts for kmeans.