Probabilistic Interval-Valued Computation: Toward a Practical Surrogate for Statistics Inside CAD Tools

Abstract

Interval methods offer a general, fine-grain strategy for modeling correlated range uncertainties in numerical algorithms. We present a new, improved interval algebra that extends the classical affine form to a more rigorous statistical foundation. Range uncertainties now take the form of confidence intervals. In place of pessimistic interval bounds, we… (More)
DOI: 10.1145/1146909.1146955

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