Generating random numbers from multiple distributions

R includes routines to generate random numbers from many distributions. Different distributions require different algorithms to generate random numbers. In essence, all random number generation routines rely on a uniform random number generator that generates an output between (0,1), and then some procedure that transform this number according to the density  that we need. 

There are several ways of doing this, depending on which distribution we want to generate. A very simple one, which works for a large amount of cases is the inverse transformation method. The idea is to generate uniform random numbers, and find the corresponding quantile for the distribution that we want to sample from. ...

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