A method for making inferences about the components of a generalized additive model is described. It is found that a variation of the method, based on means, performs well in simulations. Unlike many other inferential methods, switching from a mean to a 20% trimmed mean was found to offer little or no advantage in terms of both power and controlling the probability of a Type I error.
Wilcox, Rand R.
"Inferences About the Components of a Generalized Additive Model,"
Journal of Modern Applied Statistical Methods:
2, Article 3.
Available at: http://digitalcommons.wayne.edu/jmasm/vol5/iss2/3