Virtual population generation, fitting, and benchmarking.

A repository providing simple techniques and examples of generating random numbers from specified distributions.

This project focuses on applying advanced simulation methods for derivatives pricing. It includes Monte-Carlo, Variance Reduction Techniques, Distribution Sampling Methods, Euler Schemes, and Milstein Schemes.

Acceptance-Rejection sampling with examples in R and Python

Check if you'll get accepted into the TUM

Inverse Transform & Rejection Sampling with prob. density functions f(x) and validation functions t(x).