Publication Date



Technical Report: UTEP-CS-13-32a

To appear in Proceedings of 3rd World Conference on Soft Computing, San Antonio, December 15-18, 2013.


Measurements are never absolutely accurate; so, it is important to estimate how the measurement uncertainty affects the result of data processing. Traditionally, this problem is solved under the assumption that the probability distributions of measurement errors are normal -- or at least are concentrated, with high certainty, on a reasonably small interval. In practice, the distribution of measurement errors is sometimes heavy-tailed, when very large values have a reasonable probability. In this paper, we analyze the corresponding problem of estimating the tail of the result of data processing in such situations.

tr13-32.pdf (75 kB)
Original file: UTEP-CS-13-32