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Computing Statistics under Interval Uncertainty: Case of Relative Accuracy

  • Hung T. Nguyen
  • Vladik Kreinovich
  • Berlin Wu
  • Gang Xiang
Part of the Studies in Computational Intelligence book series (SCI, volume 393)

Abstract

Formulation of the problem. In the previous chapters, we have shown that for many statistical characteristics C, computing them with a given absolute accuracy ε – i.e., computing a value \(\tilde{C}\) for which |\(\tilde{C}\) – C| ≤ ε is NP-hard.

It turns out that if we are interested in computing these characteristics with relative accuracy – relative with respect to, e.g., the largest of the inputs – then it often possible to estimate these characteristics in polynomial time. These results first appeared in [57, 176].

Keywords

Arithmetic Operation Relative Accuracy Interval Uncertainty Computational Step Interval Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hung T. Nguyen
    • Vladik Kreinovich
      • Berlin Wu
        • Gang Xiang

          There are no affiliations available

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