Monte Carlo simulation is a powerful technique for decision analysis, but it can also be challenging to account for the correlation and dependence among the variables that affect the outcome.

Learn how to avoid algorithm errors using Monte Carlo simulation, a technique for generating random samples and estimating unknown outcomes. Implement it using Python and explore its applications ...

The key feature of a Monte Carlo simulation is that it can tell you – based on how you create the ranges of estimates – how likely the resulting outcomes are. In a Monte Carlo simulation, a random ...

Monte Carlo VaR: Generate random numbers under uniform distribution which are independent with each other and use inverse norm cdf to convert them to standard normal distribution. Combine the random ...

A set of python-based Monte Carlo tools for jet physics, including Monte Carlo integration, parton showering, and examples. The tools in this repository are designed in particular to produce ...