
Hi,

that was really helpful about the simulation. Im now trying to find (n−1)S2/σ2, 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.Ellison@lgc.co.uk
> To: konk2001@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 <konk2001@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?
> 
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