The Art of R Programming

Thus the expressionrow(m) == col(m)in the same line returns a matrix

ofTRUEandFALSEvalues,TRUEvalues on the diagonal of the matrix andFALSE

values elsewhere. Once again, keep in mind that binary operators—in this

case,==—are functions. Of course,row()andcol()are functions too, so this

expression:

row(m) == col(m)

applies that function to each element of the matrixm, and it returns a

TRUE/FALSEmatrix of the same size asm. Theifelse()expression is another

function call.

ifelse(row(m) == col(m),1,rho)

In this case, with the argument being theTRUE/FALSEmatrix just discussed,

the result is to place the values 1 andrhoin the proper places in our output

matrix.

3.3 Applying Functions to Matrix Rows and Columns..............................

One of the most famous and most used features of R is the*apply()family of

functions, such asapply(),tapply(), andlapply(). Here, we’ll look atapply(),

which instructs R to call a user-specified function on each of the rows or

each of the columns of a matrix.

3.3.1 Using the apply() Function.......................................

This is the general form ofapplyfor matrices:

apply(m,dimcode,f,fargs)

where the arguments are as follows:

• mis the matrix.


• dimcodeis the dimension, equal to 1 if the function applies to rows or 2
  for columns.


• fis the function to be applied.


• fargsis an optional set of arguments to be supplied tof.

For example, here we apply the R functionmean()to each column of a

matrixz:

>z

[,1] [,2]

[1,] 1 4

[2,] 2 5

[3,] 3 6

70 Chapter 3