On possibilistic mean value and variance of fuzzy numbers
By Christer Carlsson, R. Fullér. 1999
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Xingyu Zhou
- Zhisong Pan
- Guyu Hu
- Siqi Tang
- Aerambamoorthy Thavaneswaran
- Cheng Zhao
- Srimantoorao S. Appadoo
- A. Paseka
Citations in the corpus
- Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018, background): “Carlsson and Fullér [29] were the first to study the fuzzy real options and Thavaneswaran et al. [30] demonstrated the superiority of the fuzzy forecasts and then derived the membership function for the European call price by fuzzifying the interest rate, volatility, and the initial value of the st”
- Possibility theory and statistical reasoning (2006, background): “Fullér and colleagues [9, 53] consider introducing a weighting function on [0, 1] in order to account for unequal importance of cuts when computing upper and lower expectations.”
- Uncertainty measures for interval type-2 fuzzy sets (2007, unknown): “One definition of the (possibilistic) variance of a T1 FS A is given by Carlsson and Fulle´r [10] as ‘‘ the expected value of the squared deviations between the arithmetic mean and the endpoints of its level sets ’’, i.e., where ½ a 2 ð a Þ ; a 1 ð a Þ(cid:2) is an a -cut [36] on A .”
- A possibilistic approach to selecting portfolios with highest utility score (2002, unknown): “Key words: Mean-variance analysis; Possibility distributions,”
- Fuzzy coefficient volatility (FCV) models with applications (2007, methodology): “Following Carlsson and Fuller [1], we define the possibilistic nth moment of a fuzzy random variable A, E(A n ), as E(A n ) = 1 0 a n 2 (γ ) + a n 1 (γ ) γ dγ .”
- Weighted possibilistic moments of fuzzy numbers with applications to GARCH modeling and option pricing (2009, methodology): “A fuzzy set A in Rn is said to be a convex fuzzy set if its γ -level sets A(γ ) are (crisp) convex sets for all γ ∈ [0, 1].”