Name
Title | ||
|---|---|---|
A new approach to fuzzy regression models with application to business cycle analysis |
Abstract | ||
|---|---|---|
Recently, fuzzy regression analysis has been largely applied in the modeling of economic or financial data. However, those data often exhibit certain kinds of linguistic terms, for instance: very good, a little reclining or stable, in the business cycle or the growth rate of GDP, etc. The goal of this paper is to construct a fuzzy regression model by fuzzy parameters estimation using the fuzzy samples. It deals with imprecise measurement of observed variables, fuzzy least square estimation and nonparametric methods. This is different from the assumptions as well as the estimation techniques of the classical analysis. Empirical results demonstrate that our new approach is efficient and more realistic than the traditional regression analysis. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0165-0114(01)00175-0 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
fuzzy parameter,fuzzy parameters estimation,fuzzy regression,triangular membership function,business cycle,traditional regression analysis,new approach,square estimation,methods of least square,classical analysis,financial data,fuzzy regression model,estimation technique,fuzzy regression analysis,h-cut,h -cut,fuzzy sample,business cycle analysis,membership function,parameter estimation,h,least square,regression analysis | Econometrics,Defuzzification,Regression analysis,Regression diagnostic,Fuzzy logic,Nonparametric statistics,Adaptive neuro fuzzy inference system,Fuzzy control system,Membership function,Mathematics | Journal |
Volume | Issue | ISSN |
130 | 1 | Fuzzy Sets and Systems |
Citations | PageRank | References |
24 | 1.38 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Berlin Wu | 1 | 123 | 15.28 |
| Neng-Fang Tseng | 2 | 25 | 1.85 |