Asymptotic algorithm for computing the sample variance of interval data

被引：0
作者：
Kolacz, A. [1 ]
Grzegorzewski, P. [1 ,2 ]
机构：
[1] Warsaw Univ Technol, Fac Math & Informat Sci, Koszykowa 75, PL-00662 Warsaw, Poland
[2] Polish Acad Sci, Syst Res Inst, Newelska 6, PL-01447 Warsaw, Poland
来源：
IRANIAN JOURNAL OF FUZZY SYSTEMS | 2019年 / 16卷 / 04期
关键词：
Data analysis; interval data; sample variance; DISCRIMINANT-ANALYSIS; UNCERTAINTY; REGRESSION;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The problem of the sample variance computation for epistemic interval-valued data is, in general, NP-hard. Therefore, known efficient algorithms for computing variance require strong restrictions on admissible intervals like the no-subset property or heavy limitations on the number of possible intersections between intervals. A new asymptotic algorithm for computing the upper bound of the sample variance in a feasible time is proposed. Conditions required for its application with finite samples are discussed and some properties of the algorithm are also given. It appears that our new algorithm could be effectively applied in definitely more situations than methods used so far.
引用
收藏
页码：83 / 96
页数：14
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