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.


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.

| cite | improve this answer | |

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.