New algorithms for statistical analysis of interval data

Abstract

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. © Springer-Verlag Berlin Heidelberg 2006.