As a general rule, the distribution functions that start with p (e.g. pnorm, pexp, pgamma, ...) will transform a random variable from the corresponding distribution to a uniformly distributed random variable. The functions that start with q (e.g. qnorm, qexp, qgamma, ...) will transform a uniform random variable to the corresponding distribution. So going via the uniform distribution you can convert any distribution to another one (provided the functions exist and you have the correct one to begin with). If there is not a built in function for your distribution then you can create the appropriate distributions from the cumulative distribution function and the inverse cumulative distribution function (the distr package and friends could be of help).
But in practice if you just want to generate data from a distribution you should look at the r functions (rnorm, rexp, regamma, ...). On Mon, Nov 4, 2013 at 12:14 PM, b. alzahrani <cs_2...@hotmail.com> wrote: > > Hi guys > > Given a exponential curve, is there any function on r that can generate > exponential distributed random numbers? > > in General I want an function that can transform one probability distribution > into another?? > > Regards > ****************************************************************** > Bander > ************************************* > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
