Semi-parametric of sample selection model using fuzzy concepts


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Muhamad Safiih L., KAMIL A. A., Abu Osman M.

Journal of Modern Applied Statistical Methods, vol.8, no.2, pp.547-559, 2009 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 8 Issue: 2
  • Publication Date: 2009
  • Doi Number: 10.22237/jmasm/1257034680
  • Journal Name: Journal of Modern Applied Statistical Methods
  • Journal Indexes: Scopus
  • Page Numbers: pp.547-559
  • Keywords: Crisp data, Fuzzy sets, Membership function, Semi-parametric sample selection model, Uncertainty
  • Istanbul Gelisim University Affiliated: No

Abstract

The sample selection model has been studied in the context of semi-parametric methods. With the deficiencies of the parametric model, such as inconsistent estimators, semi-parametric estimation methods provide better alternatives. This article focuses on the context of fuzzy concepts as a hybrid to the semiparametric sample selection model. The better approach when confronted with uncertainty and ambiguity is to use the tools provided by the theory of fuzzy sets, which are appropriate for modeling vague concepts. A fuzzy membership function for solving uncertainty data of a semi-parametric sample selection model is introduced as a solution to the problem. © 2009 JMASM, Inc.