DocumentCode :
3031623
Title :
Computing Statistical Characteristics When We Know Probabilities with Interval or Fuzzy Uncertainty: Computational Complexity
Author :
Xiang, Gang ; Hall, Jim W.
Author_Institution :
Univ. of Texas at El Paso El Paso, El Paso
fYear :
2007
fDate :
24-27 June 2007
Firstpage :
576
Lastpage :
581
Abstract :
In traditional statistics, we usually assume that we know the exact probability distributions. In practice, we often only know the probabilities with interval uncertainty. The main emphasis on taking this uncertainty into account has been on situations in which we know a cumulative distribution function (cdf) with interval uncertainty. However, in some cases, we know the probability density function (pdf) with interval uncertainty. We show that in this situations, the exact range of some statistical characteristics can be efficiently computed. Surprisingly, for some other characteristics, similar statistical problems which are efficiently solvable for interval-valued cdf become computationally difficult (NP-hard) for interval-valued pdf.
Keywords :
computational complexity; fuzzy set theory; statistical distributions; NP-hard problem; computational complexity; cumulative distribution function; fuzzy uncertainty; interval uncertainty; probability density function; probability distribution; statistical characteristics; Civil engineering; Computational complexity; Computer science; Distributed computing; Fuzzy sets; Geology; Probability density function; Probability distribution; Statistical distributions; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 2007. NAFIPS '07. Annual Meeting of the North American
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-1213-7
Electronic_ISBN :
1-4244-1214-5
Type :
conf
DOI :
10.1109/NAFIPS.2007.383904
Filename :
4271127
Link To Document :
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