Análisis de regresión con datos imprecisosun nuevo enfoque que utiliza distancias difusas y sus aplicaciones

Laburpena

Regression analysis is a powerful statistical tool which has many applications in different areas. This problem under a fuzzy environment has been treated in the literature from different points of view and considering a variety of input/ output data (crisp or fuzzy). In this study we present a new methodology based on a family of fuzzy distance measures between arbitrary fuzzy numbers which involve some of the most important possibilistic and geometric characteristics of any fuzzy number. Next in this context and using the method of least squares we propose a new fuzzy regression technique to solve linear and non-linear problems. This estimation process, in general, can be considered easy to apply in practical situations and it is not limited to triangular fuzzy numbers. Finally, numerical examples are provided to illustrate its usefulness and applicability.