# diagonals in a network

A typical example in which `diagonals`

can be helpful is Social Network
Analysis. For example, if we use matrices to represent friendship
perceptions between individuals, then we need a dyadic matrix.

Let says that we want to look at second-order connections (i.e. friends
of friends). If we now want to represent the data from both time period
in a single object, we need a **4-dimensional array**. Higher-order arrays
are hard to visualise, another way of doing this is by representing two
dimensions along each of the two edges of a matrix. We can do this using
the **Knonecker Product** (denoted ⊗), which we can call in `R`

using
the alias `%x%`

.

Feelings of friendship towards oneself aren’t always particularly
insightful. We can now use the `diagonals`

library to eliminate those.

The diagonals package now available on CRAN and can therefore be install directly from inside `R`

using:

Subsequently the package can be loaded using:

The above demonstration is also available as a vignette that is included in the package.
It can be accessed from `R`

using:

A general introduction to `diagonals`

is available in next weeks post: diagonals. This post is also available as a vignette that is included in the package

For more information on the package and its development please see yesterday’s post diagonals on CRAN.