ypothesis and a good understanding
> of how the data was generated, it is impossible for you (and anyone else) to
> say how such a test might be designed.
>
> Michael
>
>
> > -Original Message-
> > From: Ogbos Okike
> > Sent: Mittwoch, 27. Februar 2019 22:53
>
From: Ogbos Okike
> Sent: Mittwoch, 27. Februar 2019 22:53
> To: Meyners, Michael
> Cc: r-help
> Subject: Re: [R] Randomization Test
>
> Dear Kind List,
>
> I am still battling with this. I have, however, made some progress with the
> suggestions of Micheal and othe
;>
>> I have not really got any response other than yours.
>>
>> I have long before now included what I have in a paper submitted to a
>> journal.
>>
>> I am awaiting the feedback of the reviewer. I will compare the
>> comments with your input her
ller than 1/n, where n is the total number of samples you
> > looked at (including the observed one), a p value of 0 is not possible in
> > randomization tests (nor in other tests, of course).
> >
> > I hope this is helpful, but you will need to go through these
her you adhered to the principles or not, which
> is impossible for me to judge based on the information provided (and I won't
> be able to look at excessive code to check either).
>
> Michael
>
> > -Original Message-
> > From: R-help On Behalf Of Ogbos Okike
based on the information provided (and I won't be
able to look at excessive code to check either).
Michael
> -Original Message-
> From: R-help On Behalf Of Ogbos Okike
> Sent: Montag, 28. Januar 2019 19:42
> To: r-help
> Subject: [R] Randomization Test
>
>
Dear Contributors,
I conducting epoch analysis. I tried to test the significance of my
result using randomization test.
Since I have 71 events, I randomly selected another 71 events, making
sure that none of the dates in the random events corresponds with the
ones in the real event.
Following th
-
>
> - Original Message -
> *From:* Charles Determan Jr
> *To:* Silvano
> *Cc:* r-help@r-project.org
> *Sent:* Friday, August 23, 2013 11:25 AM
> *Subject:* Re: [R] Randomization
>
> Hi Silvano,
>
> How about this?
>
> id <- seq(80)
>
Hi Silvano,
How about this?
id <- seq(80)
weight <- runif(80)
# randomize 4 groups with 'sample' function
group <- sample(rep(seq(4),20))
dat <- cbind(id, weight, group)
# ordered dataset by group
res <- data.frame(dat[order(group),])
# get mean and variance for each group
aggregate(res$weight
Hi,
I have a set of 80 animals and their respective weights. I
would like create 4 groups of 20 animals so that the groups
have means and variances with values ??very close.
How can I make this randomization in R?
Thanks,
--
Silvano Cesar da Costa
Departam
On Apr 27, 2010, at 4:40 AM, Wei Lun Norphos wrote:
> Hi,
>
>
>
> I‚m new to R (just installed today) and I‚m trying to figure out how to do
> stratified randomisation using it. My google search expedition has lead me
> to believe that blockrand package will most probably be the answer to it.
>
Hi,
Im new to R (just installed today) and Im trying to figure out how to do
stratified randomisation using it. My google search expedition has lead me
to believe that blockrand package will most probably be the answer to it.
Ive played around with blockrand for awhile and tried the sample
Hi all,
I would like to know how to create n equidistant random points along a
multisegment line/object of class psp and to retrieve the coordinates of
those generated random points.
thanks
P.L.
--
View this message in context:
http://www.nabble.com/Randomization%2C-line-and-spatial-coordina
; From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
> project.org] On Behalf Of Joe Ratster
> Sent: Sunday, November 30, 2008 1:22 PM
> To: r-help@r-project.org
> Subject: [R] Randomization of a two-way ANOVA?
>
>
> Hello list,
>
> I wish to perform a randomization te
I guess I have to retract my concern regarding the use of the F-statistic in
the randomization/permutation test. The code below demonstrates concurrently
testing three statistics when normality & heterogeneity is violated. The
statistics are: F, sum-squared deviation of each group mean from the mea
The code below may not be the most optimized, but it should do the trick.
I've implemented the permutation test, which by some nomenclatures is
distinguished from the randomization test in that the latter is exhaustive
while the former is not.
I'm eager to hear the views of the list on whether the
Hello list,
I wish to perform a randomization test on the F-statistics of a 2 way ANOVA
but have not been able to find out how to do so - is there a package /
function that can perform this that I am unaware of?
FactorA has 6 levels (0,1,2,3,4,5) whereas FactorB has 3 (1,2,3). A sample:
Resp.
Johannes Hüsing wrote:
> Tom Backer Johnsen <[EMAIL PROTECTED]> [Fri, Jan 11, 2008 at 06:57:41PM CET]:
> [...]
>>> Are there something that can handle this in R?
>
> Have you considered the coin package?
I'll have a look at it.
>
>> After a few hours thinking on and off about the problem, I sus
but do a lot of the random permutations.
Hope this helps,
From: [EMAIL PROTECTED] on behalf of Tom Backer Johnsen
Sent: Fri 1/11/2008 10:57 AM
To: [EMAIL PROTECTED]
Subject: Re: [R] Randomization tests, grouped data
Tom Backer Johnsen wrote:
> The other day
On Fri, 11 Jan 2008, Johannes H??sing wrote:
Tom Backer Johnsen <[EMAIL PROTECTED]> [Fri, Jan 11, 2008 at 06:57:41PM CET]:
[...]
Are there something that can handle this in R?
Have you considered the coin package?
After a few hours thinking on and off about the problem, I suspect
that the
Tom Backer Johnsen <[EMAIL PROTECTED]> [Fri, Jan 11, 2008 at 06:57:41PM CET]:
[...]
> > Are there something that can handle this in R?
>
Have you considered the coin package?
> After a few hours thinking on and off about the problem, I suspect
> that the question may be stupid or silly (or bot
Tom Backer Johnsen wrote:
> The other day I was looking into one of the classics in resampling,
> Eugene Edgington's "Randomization Tests". This type of test is simple
> to do in R with things like a simple correlation, the sample ()
> function is perfect for the purpose.
>
> However, things a
The other day I was looking into one of the classics in resampling,
Eugene Edgington's "Randomization Tests". This type of test is simple
to do in R with things like a simple correlation, the sample ()
function is perfect for the purpose.
However, things are more complex if you have grouped da
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