in reply to Probability sum of random variables

FFRank,

I'll simply point out in the case where there are only two states (0 and 1), your calculations devolve into calculations of binomials. There are formulas for these, they can be exactly calculated without brute forcing them. What you're looking at I'd call a multinomial formula, a "generalized" binomial formula. The formula probably can be found in a decent mathematical physics text or a text on statistical mechanics, or a higher end probability text. For that matter, the multinomial formula is given here.

This of course means what you're dealing with are factorial calculations as you scale up. I think you'll lose the ability to get exact answers rapidly, though the logarithmic form of Stirling's formula may allow you approximate answers on the high end of things.

David

Update: More exact language. Binomial coefficients aren't binomial distributions. Added a link to a multinomial formula.
  • Comment on Re: Probability sum of random variables

Replies are listed 'Best First'.
Re^2: Probability sum of random variables
by FFRANK (Beadle) on Aug 31, 2007 at 20:00 UTC
    Hi David, I believe the multinomial formula does not apply here, as we deal with the probability of a sum given n trials (over the combinations of outcomes that can generate the sum over n trial).

    Given: number of trials = t, sum of random variables = Z, the discrete convolution is:

    Pr[Yt = Z] = ∑ (e = 0 .. Z) Pr[Yt-1 = Z-e] * Pr[e]

    FFRANK