Using generic functions of R, when and why?

Question

I'm developing an major upgrade to the R package, and as part of the changes I want to start using the S3 methods so I can use the generic plot, summary and print functions. But I think I'm not totally sure I understand why and when to use generic functions in general.

For example, I currently have a function called logLikSSM, which computes the log-likelihood of a state space model. Instead of using this functions, I could make function logLik.SSM or something like that, as there is generic function logLik in R. The benefit of this would be that logLik is shorter to write than logLikSSM, but is there really any other point in this?

Similar case, there is a generic function called simulate in stats package, so in theory I could use that instead of simulateSSM. But now the description of the simulate function tells that function is used to "Simulate Responses", but my function actually simulates the hidden states, so it really doesn't fit into the description of the simulate function. So probably in this case I shouldn't use the generic function right?

I apologize if this question is too vague for here.

Answer 1

The advantages of creating methods for generics from the core of R include:

1. Ease of Use. Users of your package already familiar with those generics will have less to remember making it easier to use your package. They might even be able to do a certain amount without reading the documentation. If you come up with your own names then they must discover and remember new names which is an added cognitive burden.

2. Leverage Existing Functionality. Also any other functions that make use of generics you create methods for can then automatically use yours as well; otherwise, they would have to be changed. For example, AIC uses logLik.

A disadvantage is that the generic involves the extra level of dispatch and if logLik is in the inner loop of an optimization there could be an impact (although possibly not material). In that case you could check the performance of calling the generic vs. calling the method directly and use the latter if it makes a significant difference.

Regarding the case that your function has a completely different purpose than the generic in the core of R, then it might be more confusing than helpful so you might, in that case, not create a method but have your own function name.

You might want to read the zoo Design manual (see link to zoo Design under Vignettes near the bottom of that page) which discusses the design ideas that went into the zoo package. These include the idea being discussed here.

EDIT: Added disadvantates.

Answer 2

good question.

I'll split your Question into two parts; here's the first one:

i]s there really any other point in [making functions generic]?

Well, this pattern is usually invoked when the develper doesn't know the object class for every object he/she expects a user to pass in to the method under consideration.

And because of this uncertainty, this design pattern (which is called overloading in many other languages) is invokved, and which requires R to evaluate the object class, then dispatch that object to the appropriate method given the object type.

The second part of your Question: [i]n this case I shouldn't use [the generic function] right?

To try to give you an answer useful beyond the detail of your Question, consider what happens to the original method when you call setGeneric, passing that method in.

the original function body is replaced with code for performing a top-level dispatch based on type of object passed in. This replaces the original function body, which just slides down one level so that it becomes the default method that the top level (generic) function dispatches to.

showMethods() will let you see all of those methods which are called by the newly created dispatch function (generic function).