This software provides means to aggregate several probability distributions into a single integrated one. Suppose that, several independent methods are used to observe a deterministic element and each method represents the latter as a probability distribution. Thus, we deal with a family of probability distributions providing alternative descriptions to the same object. The problem is how to combine information from the prior estimates. This package implements the posterior integration method (Kryazhimskiy, 2013), which is based on the assumption that model outcomes are mutually compatible, i.e., we should observe identical outcomes after the use of model ensemble. For comparison, an implementation of simple averaging of the input distributions is added.
Downloads
Package: modelIntegration README.md
Version: 1.0.0
Binary (Windows): modelIntegration_1.0.0.zip
Package source: modelIntegration_1.0.0.tar.gz
Manual: manual.pdf
Vignettes: Introduction to the modelIntegration Package
Acknowledgements
This work received support from the EU FP7 project COMPLEX (grant no. 308601)
References
PUBLICATIONS
COMPLEX PROJECT
Related links
International Institute for Applied Systems Analysis (IIASA)
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