I would like to announce the following talk that will be held on Tuesday July 16th 2019, at 4:30 PM, in Aula D’Antoni (1101) of the Department of Mathematics, University of Rome Tor Vergata.
Speaker: Yen-Chi Chen (University of Washington)
Title: Analyzing GPS data using density ranking
Abstract: A common approach for analyzing a point cloud is based on estimating the underlying probability density function. However, in complex datasets such as GPS data, the underlying distribution function is singular so the usual density function no longer exist. To analyze this type of data, we introduce a statistical model for GPS data in the form of a mixture model with different dimensions. To derive a meaningful surrogate of the probability density, we propose a quantity called density ranking. Density ranking is a quantity representing the intensity of observations around a given point that can be defined in a singular measure. We then show that one can consistently estimate the density ranking using a kernel density estimator even in a singular distribution such as the GPS data. We apply density ranking to GPS datasets to analyze activity spaces of individuals.
Kind regards,
Anna Vidotto