Depth
of Curve Data and Applications
Date: 17 April 2020
Time: 4:00pm
Abstract: John W. Tukey (1975) defined statistical data depth as a
function that determines the centrality of an arbitrary point with respect to a data
cloud or to a probability measure. During the last
decades, this seminal idea of data depth evolved into a powerful tool proving to be useful in various fields of science.
Recently, extending the notion of data depth to the functional setting attracted a lot of
attention among theoretical and applied statisticians. We go further and suggest a notion of
data depth suitable for data represented as curves, or trajectories, which is
independent of the parametrization. We show that our curve depth satisfies theoretical
requirements of general depth functions that are meaningful for trajectories. We apply our
methodology to diffusion tensor brain images and also hurricane tracks.
Video of the seminar:
Video of the seminar: