PUA.int: Per-edge Unweighted Average (PUA) network integration

In NetInt: Methods for Unweighted and Weighted Network Integration

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);

NetInt documentation built on June 8, 2025, 1:52 p.m.