Abstract
In low dimensions, the relatively easily implementable acceptance-rejection method for generating polyhedral convex contoured uniform distributions is compared to more sophisticated particular methods from the literature, and applied to drug combination studies. Based upon a stochastic representation, the method is extended to the general class of polyhedral convex contoured distributions of known dimension. Based upon a geometric measure representation, an algorithm for simulating corresponding probabilities of rather arbitrary random events is derived.
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