Writing user-defined functions

Writing functions in R

Although R has many built-in functions that will perform a wide variety of tasks, sooner or later most R users will want to write their own functions in R.  Essentially a function is just a small program that produces a defined output given a specified input. To take a very simple example, supposed we want to write our own function to compute the sample mean.  We do this by writing a new object called (for example) my_mean, which is now a function.

my_mean<-function(x){sum(x)/length(x)}

 The input to the function is a list of numbers x, and the function computes the mean by first computing the sum and then dividing by the number of elements (both from built-in functions).  Notice that if we simply type the function on the input line (or input it from script) we just get the function description

 > my_mean

function(x){sum(x)/length(x)}

 To actually use the function we  must provide inputs (x), so a list of numbers. For example,

> data<-c(1,2,3,4,5,5,6)

> my_mean(data)

[1] 3.714286

> 

 applies the value of a list (“data”) to the function and returns the mean. 

 More complex functions can be written that involve 2 or more inputs. For example the function

 > my_fun<-function(x,y){x*2+log(y)}

 produces the function 

You can confirm that the function produces correct results for sample data by performing these same calculations on a calculator, e.g.,

> my_fun(2,3)

[1] 5.098612

> 2*2+log(3)

Although the above examples seem somewhat trivial-- because they are-- the idea is readily extended to more important and useful applications.  Examples we will see later include;

• Functions to convert data from a file, data base, or other format to a format compatible with a program for CMR analysis (MARK, RMark)

• Functions to convert from one scale or set of measurement units to another (e.g., see the temperature conversion example)

• Functions to run a set of models on a data set and summarize the results (include plotting)

• Functions to simulate data under a specific model and then run the simulated data though an estimation program

 Next: Review Exercises