TY - JOUR
ID - 4783
TI - Asymptotic algorithm for computing the sample variance of interval data
JO - Iranian Journal of Fuzzy Systems
JA - IJFS
LA - en
SN - 1735-0654
AU - Ko lacz, A.
AU - Grzegorzewski, P.
AD - Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
Y1 - 2019
PY - 2019
VL - 16
IS - 4
SP - 83
EP - 96
KW - Data analysis
KW - interval data
KW - sample variance
DO - 10.22111/ijfs.2019.4783
N2 - The problem of the sample variance computation for epistemic inter\-val-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.
UR - https://ijfs.usb.ac.ir/article_4783.html
L1 - https://ijfs.usb.ac.ir/article_4783_ef33cad89289a1e0ff1355fd414fa459.pdf
ER -