2

Assuming the only tool for generating random numbers I have available is generating a uniformly distributed variable u on U(0,1). I want to generate a Nakagami Random Variable from it.

I know I could just plug u into the inverse CDF of the Nakagami distribution, but unfortunately, the inverse CDF isn't trivial to compute.

1
  • 1
    In the worst case one can always use an approximation of the inverse CDF combining it with a rejection function to arrive at the precise distribution. Nov 14, 2013 at 9:15

1 Answer 1

4

Which difficulties do you have computing the CDF? Special functions gamma and \Gamma are availble in scientific computing libraries.

If the CDF-based method will not do, you can generate Nagakami distributed numbers based on Gamma distributed numbers or Chi distributed numbers. The methods are described in Wikipedia:

http://en.wikipedia.org/wiki/Nakagami_distribution

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

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