Hi Richard,

As others have said, try to use the "apply" functions rather than loops.
There is also an apply function for lists, see ?lapply.  This is much more
efficient.  I also like writing my own functions.  For example:

f <- function(x) {
   x^2
}

Which can then be used by:
> f(2)
[1] 4

This is very useful if you're getting into maximum likelihood programming,
or want to use the "optim" function (for multivariate functions) or
"optimize" (for univariate functions).

Lastly, check out the R reference card.
http://cran.r-project.org/doc/contrib/Short-refcard.pdf

Regards,
Peter

On Tue, Jul 19, 2011 at 12:43, RichardLang <lang@zedat.fu-berlin.de> wrote:

> Hi everyone!
>
> I'm trying to teach myself R in order to do some data analysis. I'm a
> mathematics student and (only) familiar with matlab and latex. I'm working
> trough the "official" introduction to R at the moment, while simultaneously
> solving some exercises I found in the web. Before I post my (probably
> stupid) question, I'd like to ask you for some general advice. How do you
> work with R? Is it like in matlab, that you write your functions with a lot
> of loops etc. in a textfile and then run it? Or do you just prepare your
> data and then use the functions provided by R (plot, mean etc) to get some
> analysis? I'd be very thankfull for some of your thoughts about
> "approaches".
>
> Now the question: I'm trying to build a vector with n entries, each
> consisting of the mean of m random numbers (exponential distributed for
> example). My approach was to construct a nxm random matrix and then to
> somehow take the mean of each row. But in the mean function there is no
> parameter to do this, so the intended approach of R is probably different..
> any ideas? =)
>
> Richard
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/calculating-the-mean-of-a-random-matrix-by-row-and-some-general-questions-tp3678964p3678964.html
> Sent from the R help mailing list archive at Nabble.com.
>
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