2. Rejection sampling The rejection sampling is a basic technique used to generate observations from a distri- bution. It is also commonly called the acceptance-rejection method or "accept-reject algorithm". It is a basic unit for the modern (and very popular) sampling method Markov Chain Monte Carlo (MCMC). Given a density function f(r), the rejection sampling generates data points from this distribution using the following procedure. (i) Choose a proposal density g(x) which we know how to draw sample from (for example, g(x) can be the density of a standard normal distribution) as well as a f(I) number M 2 supI g(I) (ii) Generate a random number Y from g and another random number U from Uni f[0, 1]. (iii) If U