Abstract
This article describes the development of a GUI that addresses the challenge of eliciting dependencies between uncertain quantities elicited by experts. While software for eliciting univariate uncertainties is widely available, the mathematical complexity of multivariate dependence models makes direct elicitation difficult. To overcome this, we developed Matlatzinca,11Matlatzinca may be translated from Nahuatl (the language of the Aztecs) to English as “The people that make nets”. This is the name that the Aztecs gave to the inhabitants of the Valley of Toluca in central Mexico who were well known fishermen at the time. Our first release of a GUI for PyBANSHEE is meant for people that wish to quantify (make) Non-parametric Bayesian Networks (Nets) with expert judgments. Hence we name our GUI Matlatzinca. a GUI built on top of the Python module PyBANSHEE. The GUI facilitates the elicitation process and allows experts to model dependencies using a non-parametric Bayesian network without the need for ad hoc programming. A recent practical application shows that the developed GUI is a useful tool for performing dependence elicitations, highlighting the significance of the program for dependence assessment with expert judgment.
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