PUA.int {NetInt} | R Documentation |
Per-edge Unweighted Average (PUA) network integration
Description
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: \[D(i,j) = \lbrace d | v_i \in V^d \wedge v_j \in V^d \rbrace\]
Usage
PUA.int(...)
Arguments
... |
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. |
Value
the integrated matrix : the matrix resulting from PUA.
Examples
# 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);
[Package NetInt version 1.0.0 Index]