= Matrices =

'''Matrices''' are [[R/Vectors|vectors]] structured by dimensions.

<<TableOfContents>>

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== Usage ==

A matrix is instantiated like:

{{{
> my.matrix <- matrix(c(1, 2, 3, 4), nrow=2, ncol=2)
}}}

Note that instantiating a vector is almost always a necessary first step for instantiating a matrix. If the data is already available as a vector, try:

{{{
> my.data <- c(1,2,3,4)
> dim(my.data) <- (2,2)
}}}

If an insufficient number of values are given, the matrix is padded out by recycling values. This does mean that a matrix populated with a single value can be instantiated like:

{{{
> all.zero <- matrix(0, 2, 2)
}}}

To append a row (or to combine two vectors into a new matrix), try:

{{{
> my.matrix <- rbind(my.matrix, c(8, 9))
}}}

To append a column, try:

{{{
> my.matrix <- cbind(my.matrix, c(10, 10, 10))
}}}

To access the dimensions of a data frame, try the `dim` function.

To set names for rows or columns, use the `rownames` and `colnames` functions.

Matrices are indexed in the exact same manner as [[R/Vectors|vectors]], except that a pair (row then column) is required.

{{{
> top.left <- my.matrix[1,1]
}}}

To select an entire row or column, try:

{{{
> my.row <- my.matrix[1,]
> my.col <- my.matrix[,1]
}}}

The `diag` function is heavily overloaded with meaning.

{{{
> my.vector <- diag(my.matrix)  # returns the diagonal of the matrix
> i3 <- diag(3)                 # returns the 3x3 identity matrix
> diag(i3) <- my.vector         # overwrites the diagonal of the matrix
}}}

Lastly, note these functions and [[R/Operators|operators]] for math:
 * `%*%` for multiplication
 * `tr()` for [[LinearAlgebra/Transposition|transposition]]
 * `det()` for calculating the [[LinearAlgebra/Determinant|determinant]]
 * `solve()` for [[LinearAlgebra/Invertibility|inversion]]



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CategoryRicottone