Hi,
that was really helpful about the simulation. Im now trying to find
(nâ1)S2/Ï2, and fit it to a chi squared dist with 5 degrees of freedom.
im having trouble with the coding for this. i think for the second part of that
i need to use the fitdist function, but to get it to where i am able to do
that, im not sure what to do.
THis is what i have been trying to do so far, but it hasn't returned me
anything good
sum((x-mean(x))^2)/(length(x)-1)
i am really confused, can someone please help?
Cheers
ps. if someone knows of a simpler way of creating the simulation in the first
place, your input is highly appreciated
using your method, im getting a bit confused.
> Date: Fri, 15 May 2009 12:16:45 +0100
> From: s.elli...@lgc.co.uk
> To: konk2...@hotmail.com
> Subject: Re: [R] Simulation
>
> The tidiest way of doing something 'simple' with a set of B random
> samples of size n is often to create a matrix with b rows and n columns,
> and then use apply() with a suitable function to get the statistic of
> interest.
>
> For example, in the particular case of exp(1):
>
> samples<-matrix( rexp(1000*15), ncol=15) #generates a 1000 x 15
> matrix;
> #each row is an n=15 sample from
> exp(1)
>
> meds<-apply(samples, 1, median) #applies the function 'median' to each
> row and returns the result as a vector
>
> hist(meds)
>
> For more complex problems, write a function that can be applied to each
> row. For example, look at the distribution of the test statisic for a
> wilcoxon test of whether the medians above are centred on 1.0:
>
> medtest<-function(x) {
> wilcox.test(x, mu=1)$statistic #'statistic' is the name of the
> calculated test statistic here
> #don;t need to 'return' anything because the function returns
> #the value of the last expression evaluated.
> }
>
> medsim<-apply(samples,1, medtest)
> hist(medsim)
>
> This trick (form a matrix and use apply()) can also be used to get
> multi-parameter stats, 'cos apply will return a matrix or list if the
> function returns a vector or list.
>
> The only snag is the memory usage; for large simulations that can be a
> problem. If it is, resorting to looping is still an option.
>
> Steve E
>
> >>> Kon Knafelman <konk2...@hotmail.com> 15/05/2009 10:17 >>>
>
> hey guys, i've been following this discussion about the simulation, and
> being a beginner myself, im really unsure of the best method.
>
>
>
> I hve the same problem as the initial one, except i need 1000 samples
> of size 15, and my distribution is Exp(1). I've adjusted some of the
> loop formulas for my n=15, but im unsure how to proceed in the quickest
> way.
>
>
>
> Can someone please help?
>
> _________________________________________________________________
> [[elided Hotmail spam]]
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
> *******************************************************************
> This email and any attachments are confidential. Any use, copying or
> disclosure other than by the intended recipient is unauthorised. If
> you have received this message in error, please notify the sender
> immediately via +44(0)20 8943 7000 or notify postmas...@lgc.co.uk
> and delete this message and any copies from your computer and network.
> LGC Limited. Registered in England 2991879.
> Registered office: Queens Road, Teddington, Middlesex, TW11 0LY, UK
_________________________________________________________________
Looking to change your car this year? Find car news, reviews and more
http://a.ninemsn.com.au/b.aspx?URL=http%3A%2F%2Fsecure%2Dau%2Eimrworldwide%2Ecom%2Fcgi%2Dbin%2Fa%2Fci%5F450304%2Fet%5F2%2Fcg%5F801459%2Fpi%5F1004813%2Fai%5F859641&_t=762955845&_r=tig_OCT07&_m=EXT
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
