fuzzy random variables;
fuzzy numbers;
fuzzy least squares estimation;
fuzzy autoregressive model;
fuzzy set;
D O I:
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摘要:
In this paper, we extend the standard autoregressive model to the case where the explanatory and response variables are random fuzzy variables. The fuzzy least-squares estimators (FLSE) of the model parameters are derived and their asymptotic properties are established. A simulation is conducted to evaluate our method, and it is found that the proposed method provides a better performance.
机构:
Dipartimento di Scienze Sociali ed Economiche, Sapienza-Università di Roma, P.za Aldo Moro, 5Dipartimento di Scienze Sociali ed Economiche, Sapienza-Università di Roma, P.za Aldo Moro, 5
D'Urso P.
Massari R.
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机构:
Dipartimento di Scienze Sociali ed Economiche, Sapienza-Università di Roma, P.za Aldo Moro, 5Dipartimento di Scienze Sociali ed Economiche, Sapienza-Università di Roma, P.za Aldo Moro, 5
机构:
Faculty of Geomatics,East China Institute of Technology
Jiangxi Province Key Lab for DigitalFaculty of Geomatics,East China Institute of Technology
机构:
East China Inst Technol, Fac Geomat, Nanchang 330013, Jiangxi, Peoples R China
Jiangxi Prov Key Lab Digital Land, Fuzhou 344000, Fujian, Peoples R ChinaEast China Inst Technol, Fac Geomat, Nanchang 330013, Jiangxi, Peoples R China
机构:
Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R China
Li, Dong
Li, Wai Keung
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机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R China
Li, Wai Keung
Ling, Shiqing
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机构:
Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R China