R Programming week2 Control Structures


Control Structures

Control structures in R allow you to control the flow of execution of the program, depending on

runtime conditions. Common structures are:

if, else: testing a condition

for: execute a loop a fixed number of times

while: execute a loop while a condition is true

repeat: execute an infinite loop

break: break the execution of a loop

next: skip an interation of a loop

return: exit a function


Most control structures are not used in interactive sessions, but rather when writing functions or

longer expresisons

Control Structures: if


if(<condition>) { ## do something

} else { ## do something else


if(<condition1>) { ## do something

} else if(<condition2>) { ## do something different

} else { ## do something different



if(x > 3) {

 y <- 10

} else {

 y <- 0


Of course, the else clause is not necessary

if(<condition1>) {


if(<condition2>) {



for loops take an interator variable and assign it successive values from a sequence or vector. For loops are most commonly used for iterating over the elements of an object (list, vector, etc.)

for(i in 1:10) {



This loop takes the i variable and in each iteration of the loop gives it values 1, 2, 3, ..., 10, and then exits.

These following loops have the same behavior:

x <- c("a", "b", "c", "d")

for(i in 1:4) {



for(i in seq_along(x)) {



for(letter in x) {



for(i in 1:4) print(x[i])

Nested for loops

for loops can be nested.

x <- matrix(1:6, 2, 3)

for(i in seq_len(nrow(x))) {

 for(j in seq_len(ncol(x))) {

 print(x[i, j])



Be careful with nesting though. Nesting beyond 2–3 levels is often very difficult to read/understand


While loops begin by testing a condition. If it is true, then they execute the loop body. Once the loop body is executed, the condition is tested again, and so forth

count <- 0

while(count < 10) {


 count <- count + 1


While loops can potentially result in infinite loops if not written properly. Use with care!

Sometimes there will be more than one condition in the test

z <- 5

while(z >= 3 && z <= 10) {


 coin <- rbinom(1, 1, 0.5)

 if(coin == 1) { ## random walk

 z <- z + 1

 } else {

 z <- z - 1



Conditions are always evaluated from left to right.


Repeat initiates an infinite loop; these are not commonly used in statistical applications but they do have their uses. The only way to exit a repeat loop is to call break.

x0 <- 1

tol <- 1e-8

repeat {

 x1 <- computeEstimate()

 if(abs(x1 - x0) < tol) {


 } else {

 x0 <- x1



The loop in the previous slide is a bit dangerous because there’s no guarantee it will stop. Better to set a hard limit on the number of iterations (e.g. using a for loop) and then report whether convergence was achieved or not.

next, return

next is used to skip an iteration of a loop

for(i in 1:100) {

 if(i <= 20) {

 ## Skip the first 20 iterations



 ## Do something here


return signals that a function should exit and return a given value


Control structures like if, while, and for allow you to control the flow of an R program

Infinite loops should generally be avoided, even if they are theoretically correct.

Control structures mentiond here are primarily useful for writing programs; for command-line interactive work, the *apply functions are more useful.