HWA-LUNG YUKu, Shang-JenShang-JenKuKolovos, AlexanderAlexanderKolovos2018-09-102018-09-102012http://www.scopus.com/inward/record.url?eid=2-s2.0-84872821266&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/373014Stochastic analysis and prediction is an important component of space-time data processing for a broad spectrum of Geographic Information Systems scientists and end users. For this task, a variety of numerical tools are available that are based on established statistical techniques. We present an original software tool that implements stochastic data analysis and prediction based on the Bayesian Maximum Entropy methodology, which has attractive advanced analytical features and has been known to address shortcomings of common mainstream techniques. The proposed tool contains a library of Bayesian Maximum Entropy analytical functions, and is available in the form of a plugin for the Quantum GIS open source Geographic Information System software.BME; modeling; prediction; spatiotemporal analysis; stochastic processesconference paper10.1145/2424321.2424424