Response
Parameters
the name of the response in the model
the right-hand side value
the type of inequality (less-than or greater-than)
the constraint's target. A parameter often used by solver methods that behaves as a cut-off point between desirable and unacceptable systems
the constraint's tolerance. A parameter often used by solver methods that specifies how much we are willing to be off from the target. Similar to an indifference parameter.
an optional penalty function for the constraint
true when each replication's response is 0 or 1 (the event happened or it did not), so that the estimate is a proportion and the average times the count is the number of replications in which the event happened. Feasibility is then tested with the exact (Clopper-Pearson) binomial bound instead of a normal-theory interval. That matters most when the event is rare: zero events in 30 replications has a sample variance of zero, and the normal-theory interval then has zero width and certifies the constraint with no evidence at all, while the exact bound at 95% is about 0.095.