  Transportation distance information is a powerful resource, but location
records are often censored due to privacy concerns or regulatory mandates. We
outline methods to approximate, sample from, and compare distributions of
distances between censored location pairs, a task with applications to public
health informatics, logistics, and more. We validate empirically via simulation
and demonstrate applicability to practical geospatial data analysis tasks.
