On Jul 19, 2011, at 2:43 PM, RichardLang 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".
In R one generally tries to avoid loops. There are many functions that
accept vector and matrix arguments and retrun similarly structured
results. My impression was that that was also true in Matlab and that
many of the loop-less (the R term is "vectorized") constructs were
very similar. Matrix math and all that jazz.
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? =)
Generally when performing a repeated task involving random simulation
one turns to the replicate function. To generate 5 means of length 10,
random exponentially distributed vectors:
> replicate(5, mean( rexp(10, rate= 1.5) ) )
[1] 1.0786732 0.7196179 0.7179612 0.5024858 0.4624592
--
David.
Richard
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