# Matrices in R

In this recipe, we will dive into R's capability with regard to matrices.

## How to do it…

A vector in R is defined using the `c()`

notation as follows:

vec = c(1:10)

A vector is a one-dimensional array. A matrix is a multidimensional array. We can define a matrix in R using the `matrix()`

function. Alternatively, we can also coerce a set of values to be a matrix using the `as.matrix()`

function:

mat = matrix(c(1,2,3,4,5,6,7,8,9,10),nrow = 2, ncol = 5) mat

To generate a transpose of a matrix, we can use the `t()`

function:

t(mat) # transpose a matrix

In R, we can also generate an identity matrix using the `diag()`

function:

d = diag(3) # generate an identity matrix

We can nest the `rep ()`

function within `matrix()`

to generate a matrix with all zeroes as follows:

zro = matrix(rep(0,6),ncol = 2,nrow = 3 )# generate a matrix of Zeros zro

## How it works…

We can define our data in the `matrix ()`

function by specifying our data as its first argument. The `nrow`

and `ncol`

arguments are used to specify the number of rows and column in a matrix. The `matrix`

function in R comes with other useful arguments and can be studied by typing `?matrix`

in the R command window.

The `rep()`

function nested in the `matrix()`

function is used to repeat a particular value or character string a certain number of times.

The `diag()`

function can be used to generate an identity matrix as well as extract the diagonal elements of a matrix. More uses of the `diag()`

function can be explored by typing `?diag`

in the R console window.

The code file provides a lot more functions that can used along with matrices—for example, functions related to finding a determinant or inverse of a matrix and matrix multiplication.