  The method of extended maximum likelihood is a well known concept of
parameter estimation. One can implement external knowledge on the unknown
parameters by multiplying the likelihood by constraint terms. In this note, we
emphasize that this is also true for yield parameters in an extended maximum
likelihood fit, which is widely used in the particle physics community. We
recommend a way to generate pseudo-experiments in presence of constraint terms
on yield parameters, and point to pitfalls inside the RooFit framework.
