[R] sample variance from simulation

[Mike Lawrence]

why not simply

vars=list()
for (i in 1:1000) vars[[i]] = var(z[[i]])


On Mon, May 18, 2009 at 6:51 AM, Kon Knafelman <konk2001 at hotmail.com> wrote:
>
> Hi,
>
>> g=list()
>> for(i in 1:1000){z[[i]]=rnorm(15,0,1)}
>
> I've attempted a similar problem based on the above method. Now, if i want to find the sample variance, do i go about it like this?
>
>> for (i in 1:1000)vars[[i]] = sum(z[[i]])
>> vars[[i]]
>
> the overall sigma squared will just be 1, because the distribution is standard normal. Is this correct?
>
> if so, then to find (n-1)S^2/σ^2,
>
> i will need s=999*sum(vars[[i]]))/1?
>
> Is this correct, or am i getting lost along the way?
>
> Thank you
>> Date: Wed, 13 May 2009 16:45:22 +0100
>> From: b.rowlingson at lancaster.ac.uk
>> To: csardi at rmki.kfki.hu
>> CC: r-help at r-project.org
>> Subject: Re: [R] Simulation
>>
>> On Wed, May 13, 2009 at 4:26 PM, Gábor Csárdi <csardi at rmki.kfki.hu> wrote:
>> > On Wed, May 13, 2009 at 5:13 PM, Debbie Zhang <debbie0621 at hotmail.com> wrote:
>> >>
>> >>
>> >> Dear R users,
>> >>
>> >> Can anyone please tell me how to generate a large number of samples in R, given certain distribution and size.
>> >>
>> >> For example, if I want to generate 1000 samples of size n=100, with a N(0,1) distribution, how should I proceed?
>> >>
>> >> (Since I dont want to do "rnorm(100,0,1)" in R for 1000 times)
>> >
>> > Why not? It took 0.05 seconds on my 5 years old laptop.
>>
>>  Second-guessing the user, I think she maybe doesn't want to type in
>> 'rnorm(100,0,1)' 1000 times...
>>
>>  Soln - "for" loop:
>>
>>  > z=list()
>>  > for(i in 1:1000){z[[i]]=rnorm(100,0,1)}
>>
>> now inspect the individual bits:
>>
>>  > hist(z[[1]])
>>  > hist(z[[545]])
>>
>> If that's the problem, then I suggest she reads an introduction to R...
>>
>> Barry
>>
>> ______________________________________________
>> R-help at 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.
>
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> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
>
>



-- 
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University

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~ Certainty is folly... I think. ~