See Duncan Murdoch's post here for some pointers as well as an
explanation of why this isn't a totally well-formed question:
http://r.789695.n4.nabble.com/generate-two-sets-of-random-numbers-that-are-correlated-td3736161.html
(Specifically, the post at 1:33, but it may be worthwhile to read the
w
Dear All
I need to generate multivariate NON-NORMAL data in R, which follows a
given mean vector and covariance matrix, say multivariate exponential
data. How can I do that?
Best regards
mra
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R-help@r-project.org mailing list
https://stat.ethz.ch/mai
R can tell you how many possible answers there are with those givens though:
?Inf
Really though, you can get at some information if you are willing to set one
of those definitively. I.e. If you set sample size you can 'find' data which
match specs but isn't going to be applicable to anything
Hi: I don't know if this is what you meant but here's a way to cheat and do it.
1) back out the [sigma over sqrt root of n] from the 95 % CI and call it X.
2) then generate data using rnorm(n*, known mean, sigma*)
where sigma*/sqrt(n*) = X is satisfied.
3) there will be many solutions to 2) so
On 08/09/11 09:51, Tyler Hicks wrote:
Is there a function in R that will generate data from a known mean and 95% CI?
I do not know the distribution or sample size of the original data.
No. R is wonderful, but it cannot work magic.
cheers,
Rolf Turner
___
Is there a function in R that will generate data from a known mean and 95% CI?
I do not know the distribution or sample size of the original data.
Cheers,
Tyler L Hicks
PhD Student
Washington State University - Vancouver
E-mail: tyler_hi...@wsu.edu
Website: www.thingswithwings.org
"Back of
n...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Jim Silverton
> Sent: Wednesday, January 06, 2010 1:17 AM
> To: r-help@r-project.org
> Subject: Re: [R] Generating data from Null Distribution
>
> Hello everyone,
>
> Can someone tell me exactly ho
Jim
the 2x2 case is reasonably straightforward because the support
is quite a small set.
With the aylmer package you could do this:
> a <- matrix(c(1,5,7,8),2,2)
> sample(seq_along(allprobs(a)),100,replace=TRUE,prob=allprobs(a))
[1] 3 2 4 1 3 4 4 4 4 3 3 4 4 2 3 4 5 4 3 3 4 4 2 1 4 3 3 3 4 2
Hello everyone,
Can someone tell me exactly how to generate data from a null distribution
for the fisher exact test? I know I have to use the hypergrometric but
exactly what commands do I use?
Jim
[[alternative HTML version deleted]]
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R-help
This sounds rather like homework. If so, then talk to your instructor for
help.
Otherwise:
First you go to R Site Search at http://finzi.psych.upenn.edu/search.html
or to google.
Then you search for "normal distribution".
Then you search for "plot".
Then you search for "cluster".
If you have pr
How do I simulate data with 100 points from a normal distribution with n=200,
mean (5,0), and Σ=matrix(1,0,0,0.1). After how do I plot the dataset and
include cluster centers found?
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View this message in context:
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Sent from the R he
Brett Magill sbcglobal.net> writes:
>
> Are there any R packages that could be used to generate random data given a
> set of parameters? Or, if not a package, how would one generate such data?
> What I would like to do is simulate some sample data for a regression model
> given a set of populat
Are there any R packages that could be used to generate random data given a
set of parameters? Or, if not a package, how would one generate such data?
What I would like to do is simulate some sample data for a regression model
given a set of population covariances and distribution parameters to be
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