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In many cases we use sampling from a distribution. Also in programming languages they implement it.

But I wonder now what is the process of generating a sample from a probability distribution?

What happens behind the scene that given the parameters a model, a function returns a sample?

Also how can I know more on this topic? I want to understand it clearly.

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There are at least a few methods to sample from any distribution! To begin with, one has to start with a so-called random number generator i.e one has to be able to sample from the standard uniform distribution to access the methods to sample from let's say a normal distribution. I can name some methods and I suggest reading the Wikipedia articles to start with.rejection sampling, Importance sampling, Inverse transform sampling

I also think that those are the most well-known and used. Again for all the methods, a basic random generator is required.

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