Abstract
Why indirect measurements? In many real-life situations, we are interested in the value of a physical quantity y that is difficult or impossible to measure directly. Examples of such quantities are the distance to a star and the amount of oil in a given well. Since we cannot measure y directly, a natural idea is to measure yindirectly. Specifically, we find some easier-to-measure quantities x1,…,x n which are related to y by a known relation y = f (x1,…,x n ); this relation may be a simple functional transformation, or complex algorithm (e.g., for the amount of oil, numerical solution to an inverse problem).
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Kreinovich, V. (2006). Statistical Data Processing under Interval Uncertainty: Algorithms and Computational Complexity. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_4
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DOI: https://doi.org/10.1007/3-540-34777-1_4
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