| Computing variance for interval data is NP-hard |
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ACM SIGACT News
archive
Volume 33 , Issue 2 (June 2002)
table of contents
COLUMN: Articles
table of contents
Pages: 108 - 118
Year of Publication: 2002
ISSN:0163-5700
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Authors
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Scott Ferson
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Applied Biomathematics, Setauket, NY
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Lev Ginzburg
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Applied Biomathematics, Setauket, NY
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Vladik Kreinovich
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University of Texas at El Paso, El Paso, TX
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Luc Longpré
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University of Texas at El Paso, El Paso, TX
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Monica Aviles
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University of Texas at El Paso, El Paso, TX
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Downloads (6 Weeks): 2, Downloads (12 Months): 28, Citation Count: 2
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ABSTRACT
When we have only interval ranges [xi, xi] of sample values x1,…, xn, what is the interval [V, V] of possible values for the variance V of these values? We prove that the problem of computing the upper bound V is NP-hard. We provide a feasible (quadratic time) algorithm for computing the lower bound V on the variance of interval data. We also provide a feasible algorithm that computes V under reasonable easily verifiable conditions.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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V. Kreinovich, A. Lakeyev, J. Rohn, and P. Kahl, Computational complexity and feasibility of data processing and interval computations, Kluwer, Dordrecht, 1997.
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R. Osegueda, V. Kreinovich, L. Potluri, and R. Aló, "Non-Destructive Testing of Aerospace Structures: Granularity and Data Mining Approach", Proceedings of FUZZ-IEEE'2002, Honolulu, Hawaii, May 12-17, 2002 (to appear).
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