Computational Probability

s > 4 & s < 6

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]]