Are you aware that for all the standard distributions, R provides the probability density, the cumulative distribution function, the quantile function, and random number generation? When you said, "besides uniform and gaussian", I wondered. The convention is that the first letter of the function is d, p, q, and r, for these 4 functions, followed by the name or abbreviation of the distribution. Thus, rexp = random numbers for the exponential distribution, rbeta = beta r.n., rt = Student's t, rf = F distribution, etc.
hope this helps. spencer graves
Liaw, Andy wrote:
If you can compute the quantile function of the distribution (i.e., the inverse of the integral of the pdf), then you can use the probability integral transform: If U is a U(0,1) random variable and Q is the quantile function of the distribution F, then Q(U) is a random variable distributed as F.
This is not necessarily the most efficient way of generating the random number, but it may be the only way in some cases.
HTH,
Andy
From: Yan Yu
Hello, Is there a function in R to generate random number of any given distribution (its pdf is given), besides uniform and gaussian distribution?
Thanks,
yan
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