Evaluation of Monte Carlo generation of continuous asymmetric distributions

Reliable methods for generating pseudo-random numbers from specific distributions are increasingly important in all branches of applied mathematics. In Monte Carlo studies, generating random variables from specific continuous probability distributions, whether symmetric or asymmetric is a fundamental consideration. A composite uniform U(0,1) generator algorithm is described and statistically tested. Algorithms for transforming the U(0,1) to a set of selected continuous probability distributions are also validated.