Model for the number of citations an article receives over time Is there a standard model for the number of citations an article will receive over time? If not, is there a good source for data on citation counts for articles divided up over time? Furthermore, does this vary by field

It seems plausible to me that the number of citations decays approximately exponentially, with the rate of decay depending on the article, but I have empirical evidence for this conjecture.

Such a model would be useful because a few years after an article was published, one could use the MLE method to estimate the number of citations the article would receive over any time period. This would allow us to count citations in a way that does not bias older articles, one of the chief problems with straight citation counts. Additionally, it would give us a better idea of the inaccuracies of metrics like impact factor.
I imagine you'd have an initial publication lag where citations might be lower for example in year 1 than in year 2 and that then aggregate citation counts over time would have to be monotonically decelerating. You'd also have substantial variability in terms of individual articles. For example, I've heard of articles which accelerate in their citation count over time as they become the standard citation for a particular topic.

Independent of overall number of citations received, journals and fields  differ dramatically in the rate at which citations accumulate. A good starting point is to look at "citation half life" (i.e., the median time it takes a journal or field to acquire half of its total citations). If you can access ISI you can examine how different fields and journals differ in citation half life.

For example, I just had a quick look at a few fields from ISI 2012 which yielded the following data:

Field                       Citation Half-Life (in years)
PSYCHIATRY                  7.6
ASTRONOMY &amp; ASTROPHYSICS    6.9
MATHEMATICS                 &gt;10.0
PSYCHOLOGY                  &gt;10.0


So clearly psychiatry and astronomy tend to cite more recent articles, whereas mathematics and psychology often cite older articles. 

The implication is that impact factors (which are based on the last 2 or possibly 5 years post publication) should be higher in psychiatry/astronomy than in mathematics/psychology. It also means that early career researchers in psychiatry/astronomy should accumulate a better h-index more quickly than researchers in mathematics/psychology, all else being equal.