Thanks for the reply. Does your tool assume that the variables are normally distributed for the Monte Carlo analysis you run?
It looks like your tool is closer to TopRank from Palisade in it's functionality?
It looks like your tool is closer to TopRank from Palisade in it's functionality?
This tool is a standalone thing, and you're right — it's similar to TopRank. Our actual product, Causal (https://causal.app) has aspects of @RISK, but packaged in our own (non-spreadsheet) modelling paradigm.
A previous comment mentions you are using SALib in Python, which can (even if it's not documented) use normal probability distributions for the inputs: here's a notebook with an example: https://risk-engineering.org/notebook/sensitivity-analysis.h...