Abstract
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.
DOI
10.22237/jmasm/1162353720
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
