Which packages make good use of S4 objects?

Which R packages make good use of S4 classes? I'm looking for packages that use S4 appropriately (i.e. when the complexity of the underlying problem demands), are well written and well documented (so you can read the code and understand what's going on).

I'm interested because I'll be teaching S4 soon and I'd like to point students to good examples in practice so they can read the开发者_开发问答 code to help them learn.

Thinking about this some more, maybe Matrix and/or lme4? Matrix does a lot of trickery with efficient representation of sparse matrices so this may be a worthwhile (though possibly heavy) example.

Else, given that all of BioConductor is done in S4, some of it is bound to be better than average :) I am sure Martin Morgan will pipe in with good examples.

This doesn't exactly answer your question, but....

• R in a Nutshell develops an S4 class for a timeseries object and then compares it to the S3 representation. It's a very nice illustration (without being overly complex or too simple) of the differences between S3 and S4.
• R programming for Bioinformatics briefly discusses the ExpressionSet set object.

In regards with using the Bioconductor packages, you might find that to fully appreciate the code - or even just to get started - you will have to a reasonable knowledge of biology. I suppose the same applies to complex statistics packages; you need to have a vague idea of what's going on to understand the reasons behind the code structure.

At the last LondonR meeting Brandon Whicher gave a fascinating talk about the use of S4 classes in his package dcemriS4, for use in analysing magnetic resonance imaging (MRI) in medical research.

His talk is available here: http://www.londonr.org/Medical%20Image%20Analysis%20using%20S4%20classes%20&%20methods.pdf

And the package is on CRAN: http://star-www.st-andrews.ac.uk/cran/web/packages/dcemriS4/index.html

sp and dependent packages use S4 and well documented. Alpha and omega for spatial stuff in R.

I would go for kernlab, which additionally includes a lot of C code.

It comes with an handy vignette, detailing some of S4 concepts. (It doesn't seem to use roxygen for the documentation, though, but this is not the question here.)

Trying to get a hold of the S4 system I ran across an educational package sequence. The implementation of the class system is illustrated in an accompanying set of slides in a repo roo by the same author. Though the example used is from biostatistics, it's good to follow.

It is a great learning resource, because the author took carefully contrasted the different object systems while at the same time keeping the complexity of the package adequate for learning.