Partial Linear Models With Fuzzy Data

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.

Authors

Mahdi Roozbeh

Department of Statistics, Faculty of Mathematics,Statistics and Computer Sciences

Monireh Maanavi

Semnan University, P.O. Box ۳۵۱۹۵-۳۶۳, Semnan, Iran