|
 
|
[FGS08] Inverse Regression Methods Based on Fuzzy Partitions
Revue Internationale avec comité de lecture : Journal Int. J. of Pure and Applied Mathematics, vol. 43, pp. 43-62, 2008
motcle:
Résumé:
We consider a semiparametric regression model such that
the dependent variable y is linked to some indices xÂÂŒB_k through an unknown
link function. Li (1991) introduced sliced inverse regression methods
(SIR-I, SIR-II and SIRa) in order to estimate the effective dimension
reduction space spanned by the vectors Bk. These methods computationally
fast and simple but are influenced by the choice of slices in the
estimation process. In this paper, we suggest to use versions of SIR
methods based on fuzzy clusters instead of slices which can be seen as
hard clusters and we exhibit the corresponding algorithm. We illustrate
the sample behaviour of the fuzzy inverse regression estimators
and compare them with the SIR ones on simulation study.
Equipe:
msdma
BibTeX
| @article { | |||
| FGS08, | |||
| title | = | "{Inverse Regression Methods Based on Fuzzy Partitions}", | |
| author | = | "S. Ferrigno and A. Gannoun and J. Saracco", | |
| journal | = | "Int. J. of Pure and Applied Mathematics", | |
| year | = | 2008, | |
| volume | = | 43, | |
| pages | = | "43-62", | |
| } | |||
