PUA.int {NetInt} | R Documentation |
It performs the per-edge unweighted average integration between networks: \[\bar{w}_{ij} = \frac{1}{|D(i,j)|} \sum_{d \in D(i,j)} w_{ij}^d\] where: \[D(i,j) = \lbrace d | v_i \in V^d \wedge v_j \in V^d \rbrace\]
PUA.int(...)
... |
a list of numeric matrices. These must be named matrices representing adjacency matrices of the networks. Matrices may have different dimensions, but corresponding elements in different matrices must have the same name. |
the integrated matrix : the matrix resulting from PUA.
# Create three example networks of different size
set.seed(123);
A1 <- matrix(runif(100, min = 0, max = 1), nrow = 10);
A1[lower.tri(A1)] = t(A1)[lower.tri(A1)];
diag(A1) <- 0;
rownames(A1) <- colnames(A1) <- sample(LETTERS, 10);
A2 <- matrix(runif(49, min = 0, max = 1), nrow = 7);
A2[lower.tri(A2)] = t(A2)[lower.tri(A2)];
diag(A2) <- 0;
rownames(A2) <- colnames(A2) <- rownames(A1)[1:7];
A3 <- matrix(runif(100, min = 0, max = 1), nrow = 10);
A3[lower.tri(A3)] = t(A3)[lower.tri(A3)];
diag(A3) <- 0;
rownames(A3) <- colnames(A3) <- c(rownames(A1)[1:5], c("A", "B", "Z", "K", "Q"));
# Integrate networks using Per-edge Unweighted Average (PUA) method
A_int <- PUA.int(A1, A2, A3);