Probabilities, Intervals, What Next? Optimization Problems Related to Extension of Interval Computations to Situations with Partial Information about Probabilities

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Abstract

When we have only interval ranges [x, JOURNAL/jglop/04.02/00115515-200429030-00003/OV0335/v/2017-10-11T030044Z/r/image-pngi] of sample values x1,…, xn, what is the interval [V, JOURNAL/jglop/04.02/00115515-200429030-00003/OV0413/v/2017-10-11T030044Z/r/image-png] of possible values for the variance V of these values? We show that the problem of computing the upper bound JOURNAL/jglop/04.02/00115515-200429030-00003/OV0413/v/2017-10-11T030044Z/r/image-png is NP-hard. We provide a feasible (quadratic time) algorithm for computing the exact lower bound V on the variance of interval data. We also provide feasible algorithms that computes JOURNAL/jglop/04.02/00115515-200429030-00003/OV0413/v/2017-10-11T030044Z/r/image-png under reasonable easily verifiable conditions, in particular, in case interval uncertainty is introduced to maintain privacy in a statistical database. We also extend the main formulas of interval arithmetic for different arithmetic operations x1 op x2 to the case when, ∖break for each input xi, in addition to the interval xi = [xi, JOURNAL/jglop/04.02/00115515-200429030-00003/OV0335/v/2017-10-11T030044Z/r/image-pngi] of possible values, we also know its mean Ei (or an interval Ei of possible values of the mean), and we want to find the corresponding bounds for y=x1 op x2 and its mean. In this case, we are interested not only in the bounds for y, but also in the bounds for the mean of y. We formulate and solve the corresponding optimization problems, and describe remaining open problems.

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