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.

if(<condition>) {
        ## do something
} else {
        ## do something else
}
if(<condition1>) {
        ## do something
} else if(<condition2>)  {
        ## do something different
} else {
        ## do something different
}

This is a valid if/else structure.

if(x > 3) {
        y <- 10
} else {
        y <- 0
}

So is this one.

y <- if(x > 3) {
        10
} else { 
        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) {
        print(i)
}

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

These three loops have the same behavior.

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

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

for(i in seq_along(x)) {
        print(x[i])
}

for(letter in x) {
        print(letter)
}

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

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) {
        print(count)
        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) {
        print(z)
        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) {
                break
        } 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 is used to skip an iteration of a loop

for(i in 1:100) {
        if(i <= 20) {
                ## Skip the first 20 iterations
                next 
        }
        ## Do something here
}

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

Summary

• 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.