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Breakthrough in Interval Data Fitting II. From Ranges to Means and Standard Deviations

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Warianty tytułu
Konferencja
Evolutionary Computation and Global Optimization 2009 / National Conference (12 ; 1-3.06.2009 ; Zawoja, Poland)
Języki publikacji
EN
Abstrakty
EN
Interval analysis, when applied to the so called problem of experimental data fitting, appears to be still in its infancy. Sometimes, partly because of the unrivaled reliability of interval methods, we do not obtain any results at all. Worse yet, if this happens, then we are left in the state of complete ignorance concerning the unknown parameters of interest. This is in sharp contrast with widespread statistical methods of data analysis. In this paper I show the connections between those two approaches: how to process experimental data rigorously, using interval methods, and present the final results either as intervals (guaranteed, rigorous results) or in a more familiar probabilistic form: as a mean value and its standard deviation.
Rocznik
Tom
Strony
73--78
Opis fizyczny
Bibliogr. 4 poz.
Twórcy
Bibliografia
  • [1] Marek W. Gutowski Breakthrough in Interval Data Fitting. I. The Role of Hausdorff Distance, in this proceedings.
  • [2] R.E. Moore Interval Analysis Prentice Hall, Englewood Cliffs, NJ, 1966
  • [3] A. Voschinin, N. Skibitski, Interval calibration model of multisensor system, Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS'2003. Proceedings of the Second IEEE International Workshop on. pp. 253-256
  • [4] S. Skelboe, Computation of rational interval functions, BIT 14, 87-95, 1974
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA9-0038-0009
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