> >>>>
> >>>> A simple solution is to apply a Bonferroni correction where alpha is
> >>>> divided by the number of comparisons. If there are 250, then 0.05/250 =
> >>>> 0.0002. Another approach is to try to discuss the outcomes i
t;>> great significance in the Redskins rule:
> >>>> https://en.wikipedia.org/wiki/Redskins_Rule.
> >>>>
> >>>> A simple solution is to apply a Bonferroni correction where alpha is
> >>>> divided by the number of comparisons. If there ar
2, 2022 12:07 PM
To: Ebert,Timothy Aaron
Cc: Val ; r-help@R-project.org (r-help@r-project.org)
Subject: Re: [R] Correlate
[External Email]
... But of course the p-values are essentially meaningless without some sort of
multiplicity adjustment.
(search on "multiplicity adjustment" fo
mentwise error rate previously mentioned.
>
> Large datasets can be very messy.
>
>
> Tim
>
> -Original Message-
> From: Bert Gunter
> Sent: Monday, August 22, 2022 12:07 PM
> To: Ebert,Timothy Aaron
> Cc: Val ; r-help@R-project.org (r-help@r-project.org)
>
im
-Original Message-
From: Bert Gunter
Sent: Monday, August 22, 2022 12:07 PM
To: Ebert,Timothy Aaron
Cc: Val ; r-help@R-project.org (r-help@r-project.org)
Subject: Re: [R] Correlate
[External Email]
... But of course the p-values are essentially meaningless without some sort of
multipl
Hi all,
I have a data set with ~250 variables(columns). I want to calculate
the correlation of one variable with the rest of the other variables
and also want the p-values for each correlation. Please see the
sample data and my attempt. I have got the correlation but unable to
get the p-v
Hi Ira,
I tried the ?lapply(). Looks like it edges the ?for() loop.
For e.g.
set.seed(435)
m1 <- matrix(rnorm(2000*30), ncol=30)
m2 <- matrix(rnorm(2000*30), ncol= 30)
corsP<-vector()
system.time({for(i in 1:2000) corsP[i] = cor(m1[i,], m2[i,])})
# user system elapsed
# 0.124 0.00
Hi,
You may try:
set.seed(49)
m1 = matrix(rnorm(30), nrow = 3)
m2 = matrix(rnorm(30), nrow = 3)
corsP<-vector()
for(i in 1:3) corsP[i] = cor(m1[i,], m2[i,])
corsP
#[1] 0.58411274 -0.02382329 0.03760757
diag(cor(t(m1),t(m2)))
#[1] 0.58411274 -0.02382329 0.03760757
#or
mNew<- rbind(m1,m2)
Have you looked at ts() ?
On Tue, Sep 22, 2009 at 5:49 PM, Maggie wrote:
> I was wondering how to correlate two time series in R? I have to
> plotted waver files I need to correlate to one another to see how well
> they align..
>
> Any guidance would be very much appreciated!
>
> ___
I was wondering how to correlate two time series in R? I have to
plotted waver files I need to correlate to one another to see how well
they align..
Any guidance would be very much appreciated!
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