Physics
Scientific paper
Sep 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998spie.3459..106k&link_type=abstract
Proc. SPIE Vol. 3459, p. 106-115, Bayesian Inference for Inverse Problems, Ali Mohammad-Djafari; Ed.
Physics
Scientific paper
In many real-life situations, it is very difficult or even impossible to directly measure the quantity y in which we are interested: e.g., we cannot directly measure a distance to a distant galaxy or the amount of oil in a given well. Since we cannot measure such quantities directly, we can measure them indirectly: by first measuring some relating quantities x1,...,xn, and then by using the known relation between xi and y to reconstruct the value of the desired quantity y. In practice, it is often very important to estimate the error of the resulting indirect measurement. In this paper, we show that in a natural statistical setting, the problem of estimating the error of indirect measurement can be formulated as a simplified version of a tomography problem. In this paper, we use the ideas of invariance to find the optimal algorithm for solving this simplified tomography problem, and thus, for solving the statistical problem or error estimation for indirect measurements.
Kreinovich Vladik
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