TY - JOUR UR - http://lib.ugent.be/catalog/pug01:8513248 ID - pug01:8513248 LA - eng TI - M-estimates of location for the robust central tendency of fuzzy data PY - 2016 JO - (2016) IEEE TRANSACTIONS ON FUZZY SYSTEMS SN - 1063-6706 SN - 1941-0034 PB - 2016 AU - Sinova, Beatriz AU - Ángeles Gil, María AU - Van Aelst, Stefan 801001592978 AB - The Aumann-type mean has been shown to possess valuable properties as a measure of the location or central tendency of fuzzy data associated with a random experiment. However, concerning robustness its behavior is not appropriate. The Aumann-type mean is highly affected by slight changes in the fuzzy data or when outliers arise in the sample. Robust estimators of location, on the other hand, avoid such adverse effects. For this purpose, this paper considers the M-estimation approach and discusses conditions under which this alternative yields valid fuzzy-valued M-estimators. The resulting M-estimators are applied to a real-life example. Finally, some simulation studies show-empirically the suitability of the introduced estimators. ER -Download RIS file
00000nam^a2200301^i^4500 | |||
001 | 8513248 | ||
005 | 20170509133633.0 | ||
008 | 170308s2016------------------------eng-- | ||
022 | a 1063-6706 | ||
022 | a 1941-0034 | ||
024 | a 000381582100014 2 wos | ||
024 | a 1854/LU-8513248 2 handle | ||
024 | a 10.1109/TFUZZ.2015.2489245 2 doi | ||
040 | a UGent | ||
245 | a M-estimates of location for the robust central tendency of fuzzy data | ||
260 | c 2016 | ||
520 | a The Aumann-type mean has been shown to possess valuable properties as a measure of the location or central tendency of fuzzy data associated with a random experiment. However, concerning robustness its behavior is not appropriate. The Aumann-type mean is highly affected by slight changes in the fuzzy data or when outliers arise in the sample. Robust estimators of location, on the other hand, avoid such adverse effects. For this purpose, this paper considers the M-estimation approach and discusses conditions under which this alternative yields valid fuzzy-valued M-estimators. The resulting M-estimators are applied to a real-life example. Finally, some simulation studies show-empirically the suitability of the introduced estimators. | ||
598 | a A1 | ||
100 | a Sinova, Beatriz | ||
700 | a Ángeles Gil, María | ||
700 | a Van Aelst, Stefan 0 801001592978 0 971606183994 | ||
650 | a Science General | ||
653 | a LINGUISTIC TERM SETS | ||
653 | a NUMBER-VALUED DATA | ||
653 | a TRAPEZOIDAL APPROXIMATIONS | ||
653 | a STATISTICAL-ANALYSIS | ||
653 | a RANDOM-VARIABLES | ||
653 | a RATING-SCALE | ||
653 | a PARAMETER | ||
653 | a SUPPORT | ||
653 | a Fuzzy number-valued data | ||
653 | a M-estimators | ||
653 | a random fuzzy numbers | ||
653 | a robust | ||
653 | a location of fuzzy data | ||
773 | t IEEE TRANSACTIONS ON FUZZY SYSTEMS g IEEE Trans. Fuzzy Syst. 2016. 24 (4) p.945-956 q 24:4<945 | ||
856 | 3 Full Text u https://biblio.ugent.be/publication/8513248/file/8513252 z [ugent] y 07295579.pdf | ||
920 | a article | ||
852 | x WE b WE02 | ||
922 | a UGENT-WE |
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