R help - Jun 2003 - Simulating a variable following an arbitrary distribution

Hi, I'd like to know if there's anything in R that could help me do
that. Let's suppose I have a density function of a random variable, for
example
f(x) = (x^3)/4 0 < x < 2 and I would like to simulate it. For the common
distributions (exponencial, gamma, cauchy) there are the r-functions (rgamma,
rexp, runif, rcauchy, and so on).. But when the variable I want to simulate is
not one of those, how should I procede? I read some references on the subject
and saw that there are some algorithms that can do that, but I just wonder if
there is any implemented in R?

Thank you,

--

Hi,
Use the Inverse transformation method. See any basic Cbook in simulation
for instance Sheldon Ross's book.
Regards,
Edgar

On Mon, 2 Jun 2003, Fernando Henrique Ferraz Pereira da Rosa wrote:
>      Hi, I'd like to know if there's anything in R that could help
me do
> that. Let's suppose I have a density function of a random variable, for
example
> f(x) = (x^3)/4 0 < x < 2 and I would like to simulate it. For the
common
> distributions (exponencial, gamma, cauchy) there are the r-functions
(rgamma,
> rexp, runif, rcauchy, and so on).. But when the variable I want to simulate
is
> not one of those, how should I procede? I read some references on the
subject
> and saw that there are some algorithms that can do that, but I just wonder
if
> there is any implemented in R?
>
> Thank you,
>
> --
>
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>