simdec 1.1.0

Warning This library is under active development and things can change at anytime! Suggestions and help are greatly appreciated.

Simulation decomposition or SimDec is an uncertainty and sensitivity analysis method, which is based on Monte Carlo simulation. SimDec consists of three major parts:

1. computing sensitivity indices,
2. creating multi-variable scenarios and mapping the output values to them, and
3. visualizing the scenarios on the output distribution by color-coding its segments.

SimDec reveals the nature of causalities and interaction effects in the model. See our publications and join our discord community.

Python API

The library is distributed on PyPi and can be installed with:

pip install simdec

To install the development version, download the source and from the root of the repository:

pip install -e .[dev]

Dashboard

A live dashboard is available at:

https://simdec.io

Local use

The dashboard can be run locally using:

make serve

Deployment

The live version of the dashboard is hosted on GCP. To deploy a new version:

PANEL_TOKEN=... make production

Citations

The algorithms and visualizations used in this package came primarily out of research at LUT University, Lappeenranta, Finland, and Stanford University, California, U.S., supported with grants from Business Finland, Wihuri Foundation, and Finnish Foundation for Economic Education.

If you use SimDec in your research we would appreciate a citation to the following publications:

• Kozlova, M., & Yeomans, J. S. (2022). Monte Carlo Enhancement via Simulation Decomposition: A “Must-Have” Inclusion for Many Disciplines. INFORMS Transactions on Education, 22(3), 147-159. DOI:10.1287/ited.2019.0240.
• Kozlova, M., Moss, R. J., Yeomans, J. S., & Caers, J. (forthcoming). Uncovering Heterogeneous Effects in Computational Models for Sustainable Decision-making. Environmental Modelling & Software.
• Kozlova, M., Moss, R. J., Roy, P., Alam, A., & Yeomans, J. S. (forthcoming). SimDec algorithm. In M. Kozlova & J. S. Yeomans (Eds.), Sensitivity Analysis for Business, Technology, and Policymaking Made Easy with Simulation Decomposition. Routledge.