A common problem in the operation of mission critical control systems is that of determining the future value of a physical quantity based upon past measurements of it or of related quantities. Some of the sources of variability that make this problem di cult include imprecision due to measurement error, measurements that change with time, and intermittent failures leading to faulty measurements. We present a novel solution to this problem based upon the following hypotheses: 1 Each measurement is presented as a timestamped interval that contains the correct value of the physical quantity; 2 The underlying process describing the physical quantity is linear or a low-degree polynomial; and, 3 up to f of the n measurements may be arbitrarily faulty, where n 2f + 1. For a given future time t0, our algorithm produces the smallest set of possible values that the function may take at time t0. For linear functions, our algorithm runs in time On 2 , and for degree-d polynomials it ...