Abstract
Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear ( with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.
DOI
10.33095/jeas.v14i50.1401
Subject Area
Statistical
First Page
281
Last Page
291
Recommended Citation
Rashid, D. H., & Ali, O. A. (2008). A Robust Estimator for a Generalized Semiparametric Additive Model. Journal of Economics and Administrative Sciences, 14(50), 281-291. https://doi.org/10.33095/jeas.v14i50.1401
