# User-written Functions

One of the great strengths of R is the user's ability to add functions. In fact, many of the functions in R are actually functions of functions. The structure of a function is given below.

```
myfunction <- function(arg1, arg2, ... ){
statements
return(object)
}
```

Objects in the function are local to the function. The object returned can be any data type. Here is an example.

```
# function example - get measures of central tendency
# and spread for a numeric vector x. The user has a
# choice of measures and whether the results are printed.
mysummary <- function(x,npar=TRUE,print=TRUE) {
if (!npar) {
center <- mean(x); spread <- sd(x)
} else {
center <- median(x); spread <- mad(x)
}
if (print & !npar) {
cat("Mean=", center, "\n", "SD=", spread, "\n")
}
else if (print & npar) {
cat("Median=", center, "\n", "MAD=", spread, "\n")
}
result <- list(center=center,spread=spread)
return(result)
}
# invoking the function
set.seed(1234)
x <- rpois(500, 4)
y <- mysummary(x)
Median= 4
MAD= 1.4826
# y$center is the median (4)
# y$spread is the median absolute deviation (1.4826)
y <- mysummary(x, npar=FALSE, print=FALSE)
# no output
# y$center is the mean (4.052)
# y$spread is the standard deviation (2.01927)
```

It can be instructive to look at the code of a function. In R, you can view a function's code by typing the function name without the ( ).

Finally, you may want to store your own functions, and have them available in every session. You can customize the R environmentto load your functions at start-up.