L2L.normalized: Compute normalized version of graph Laplacian matrix
In mdpeer: Graph-Constrained Regression with Enhanced Regularization Parameters Selection
Description
Usage
Arguments
Value
Examples
Description
Compute normalized version of graph Laplacian matrix
Usage
1
Arguments
L
graph Laplcian matrix
Value
normalized graph Laplacian matrix
Examples
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# Define exemplary adjacency matrix
p1 <- 10
p2 <- 40
p <- p1 + p2
A <- matrix(rep(0, p * p), p, p)
A[1:p1, 1:p1] <- 1
A[(p1 + 1):p, (p1 + 1):p] <- 1
vizu.mat(A, "adjacency matrix")
# Compute corresponding Laplacian matrix
L <- Adj2Lap(A)
vizu.mat(L, "Laplacian matrix")
# Compute corresponding Laplacian matrix - normalized
L.norm <- L2L.normalized(L)
vizu.mat(L.norm, "L Laplacian matrix (normalized)")
mdpeer documentation built on May 2, 2019, 3:36 p.m.
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Description Usage Arguments Value Examples
Description
Compute normalized version of graph Laplacian matrix
Usage
1 |
Arguments
L |
graph Laplcian matrix |
Value
normalized graph Laplacian matrix
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Define exemplary adjacency matrix
p1 <- 10
p2 <- 40
p <- p1 + p2
A <- matrix(rep(0, p * p), p, p)
A[1:p1, 1:p1] <- 1
A[(p1 + 1):p, (p1 + 1):p] <- 1
vizu.mat(A, "adjacency matrix")
# Compute corresponding Laplacian matrix
L <- Adj2Lap(A)
vizu.mat(L, "Laplacian matrix")
# Compute corresponding Laplacian matrix - normalized
L.norm <- L2L.normalized(L)
vizu.mat(L.norm, "L Laplacian matrix (normalized)")
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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