Publication Type
Conference Paper
Publication Date
Page Numbers
208 to 211
Conference Name
International Conference on GIScience (GIScience 2016)
Conference Location
Montreal, Canada
Conference Sponsor
Various
Conference Date
-
Abstract
Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.
