A Markov chain can be defined as a stochastic process Y in which the value at each point at time t depends only on the value at time t-1. It means that the probability for our stochastic process to have state x at time t, given all its past states, is equal to the probability […]

# Tag Archives: MonteCarlo

## Understanding Rejection Sampling method

Rejection sampling is a computational technique whose aim is generating random numbers from a target probability distribution f(x). It is related to the general field of MonteCarlo methods, whose core is generating repeated random sampling to make numerical estimation of unknown parameters. Some words about Randomness One might ask why a random variable with probability […]