Advanced Distribution Theory for SiZer
Jan Hannig, James Stephen Marron · Journal of the American Statistical Association · 2006
SiZer is a powerful method for exploratory data analysis. In this article approximations to the distributions underlying the simultaneous statistical inference are investigated, and large improvements are made in the approximation using extreme value theory. This results in improved size, and also in an improved global inference version of SiZer. The main points are illustrated with real data and simulated examples.