  We analyze the AneuRisk65 curvature functions using a likelihood-based
warping method for sparsely sampled curves, and combine it with logistic
regression in order to discriminate subjects with aneurysms at or after the
terminal bifurcation of the internal carotid artery (the most life-threatening)
from subjects with no aneurysms or aneurysms along the carotid artery (the less
serious). Significantly lower misclassification rates are obtained when the
warping functions are included in the logistic discrimination model, rather
than being treated as mere nuisance parameters.
