Applied fuzzy systems
A linear regression model using triangular fuzzy number coefficients
Fuzzy Sets and Systems
An epistemological comparison between fuzzy logic engines and Bayesian filters
WSEAS Transactions on Systems and Control
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The sample selection model studied in the context of semi-parametric methods. With the deficiency of the parametric model, such as inconsistent estimators etc, the semi-parametric estimation methods provide the best alternative to handle this deficiency. Semi-parametric of a sample selection model is an econometric model has been found interesting application in empirical studies. The issue of uncertainty and ambiguity still become are major problem and complicated in the modeling of semi-parametric sample selection model as well as its parametric. In this study, we will focus in the context of fuzzy concept as a hybrid to the semi-parametric sample selection model. The best approach of accounting for uncertainty and ambiguity is to take advantage of the tools provided by the theory of fuzzy sets. It seems particularly appropriate for modeling vague concepts. Fuzzy sets theory and its properties through the concept of fuzzy number provide an ideal framework in order to solve the problem of uncertainty data. In this paper, we introduce a fuzzy membership function for solving uncertainty data of a semi-parametric sample selection model.