New Algorithms for Statistical Analysis of Interval Data

نویسندگان

  • Gang Xiang
  • Scott A. Starks
  • Vladik Kreinovich
  • Luc Longpré
چکیده

It is known that in general, statistical analysis of interval data is an NP-hard problem: even computing the variance of interval data is, in general, NP-hard. Until now, only one case was known for which a feasible algorithm can compute the variance of interval data: the case when all the measurements are accurate enough – so that even after the measurement, we can distinguish between different measured values x̃i. In this paper, we describe several new cases in which feasible algorithms are possible – e.g., the case when all the measurements are done by using the same (not necessarily very accurate) measurement instrument – or at least a limited number of different measuring instruments.

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تاریخ انتشار 2004