Partial Linear Models With Fuzzy Data
Publish place: 3rd International Conference on Soft Computing
Publish Year: 1398
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSCG03_228
تاریخ نمایه سازی: 14 فروردین 1399
Abstract:
In this paper, we introduce a semiparametric ridge regression approach under imprecise circumstances. To end this purpose, A fuzzy regression model is used in evaluating the functional relationship between the dependent and independent variables in a partial linear model. Most fuzzy regression models are considered to be fuzzy outputs but crisp inputs. Thus we employ fuzzy least squares methods for the analysis for the partial linear model when the outputs are assumed to be fuzzy. To accommodate the proposed methodology for facing with sophisticated environments, some additional artificial linear restrictions are imposed to the whole parameter space. Semiparametric ridge and non-ridge fuzzy type estimators, in a restricted manifold are then defined. Asymptotic distributional bias and risk are also derived and some comparison results are given. A Monte Carlo simulation study is also conducted to estimate the parametric and non-parametric parts in the fuzzy regression model.
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Authors
Mahdi Roozbeh
Department of Statistics, Faculty of Mathematics,Statistics and Computer Sciences
Monireh Maanavi
Semnan University, P.O. Box ۳۵۱۹۵-۳۶۳, Semnan, Iran