  In this paper, we consider the situation in which the observations follow an
isotonic generalized partly linear model. Under this model, the mean of the
responses is modelled, through a link function, linearly on some covariates and
nonparametrically on an univariate regressor in such a way that the
nonparametric component is assumed to be a monotone function. A class of robust
estimates for the monotone nonparametric component and for the regression
parameter, related to the linear one, is defined. The robust estimators are
based on a spline approach combined with a score function which bounds large
values of the deviance. As an application, we consider the isotonic partly
linear log--Gamma regression model. Through a Monte Carlo study, we investigate
the performance of the proposed estimators under a partly linear log-Gamma
regression model with increasing nonparametric component.
