[R] Computational Probability

[Gabor Grothendieck]

Try a simulation approach.  vignette("rv") for more info.

> set.seed(1)
> library(rv)
> x <- rvunif(10)
> s <- simapply(x, sum)
> mean(s > 4 & s < 6)
    mean   sd 1% 2.5% 25% 50% 75% 97.5% 99% sims
[1] 0.72 0.45  0    0   0   1   1     1   1 2500



On Fri, Dec 26, 2008 at 7:42 AM, Rory Winston <rory.winston at gmail.com> wrote:
> Hi
>
> Firstly , happy Christmas to R-Help! Secondly, I wonder if anyone can help
> me with the following query: I am trying to reproduce some explicit
> probability calculations performed in APPL (a Maple extension for
> computational probability). For instance, in APPL, to compute the
> probability that the sum of 10 iid uniform variables [0,1] will be between 4
> and 6, (i..e Pr( 4 < \sum_{i=1}^{10}X_i < 6)), I can type:
>
> X := UniformRV(0, 1);
> Y := ConvolutionIID(X, 10);
> CDF(Y,6) - CDF(Y,4);
>
> which gives the required probability .7222. Is there any way to perform
> these type of calcuations in R in a general way? I realise that a lot of the
> machinery behind these computations comes from Maple's symbolic engine, but
> are there any R extensions for these kind of calculation?
>
> Cheers
> Rory
>
>        [[alternative HTML version deleted]]
>
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