# diffnetmatmult: Matrix multiplication In USCCANA/netdiffuseR: Analysis of Diffusion and Contagion Processes on Networks

## Description

Matrix multiplication methods, including `diffnet` objects. This function creates a generic method for `%*%` allowing for multiplying diffnet objects.

## Usage

 ```1 2 3 4 5 6 7``` ```x %*% y ## Default S3 method: x %*% y ## S3 method for class 'diffnet' x %*% y ```

## Arguments

 `x` Numeric or complex matrices or vectors, or `diffnet` objects. `y` Numeric or complex matrices or vectors, or `diffnet` objects.

## Details

This function can be usefult to generate alternative graphs, for example, users could compute the n-steps graph by doing `net %*% net` (see examples).

## Value

In the case of `diffnet` objects performs matrix multiplication via `mapply` using `x\$graph` and `y\$graph` as arguments, returnling a `diffnet`. Otherwise returns the default according to `%*%`.

Other diffnet methods: `as.array.diffnet()`, `c.diffnet()`, `diffnet-arithmetic`, `diffnet-class`, `diffnet_index`, `plot.diffnet()`, `summary.diffnet()`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# Finding the Simmelian Ties network ---------------------------------------- # Random diffnet graph set.seed(773) net <- rdiffnet(100, 4, seed.graph='small-world', rgraph.args=list(k=8)) netsim <- net # According to Dekker (2006), Simmelian ties can be computed as follows netsim <- net * t(net) # Keeping mutal netsim <- netsim * (netsim %*% netsim) # Checking out differences (netsim should have less) nlinks(net) nlinks(netsim) mapply(`-`, nlinks(net), nlinks(netsim)) ```