Hi everyone.
I'm using matrix product such as :
#Generate some data
NCols = 5
NRows = 5
A = matrix(runif(NCols*NRows), ncol=NCols)
B = matrix(runif(NCols*NRows), ncol=NCols)
#First calculation
R = A%*%B
for(i in 1:100)
{
R = R%*%B
}
I would like to know if it was possible to
Hi:
Try the expm package. Using your example,
R = A%*%B
for(i in 1:100)
+ {
+R = R%*%B
+ }
R
[,1] [,2] [,3] [,4] [,5]
[1,] 9.934879e+47 1.098761e+48 8.868476e+47 7.071831e+47 6.071370e+47
[2,] 1.492692e+48 1.650862e+48 1.332468e+48
Hi sire.
This is exactly what I was looking for, thank you.
With regards,
Phil
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Thanks for your help.
Date: Mon, 2 Nov 2009 18:50:42 -0500
Subject: Re: [R] avoiding loop
From: jholt...@gmail.com
To: bbom...@hotmail.com
CC: mtmor...@fhcrc.org; r-help@r-project.org
The first thing I would suggest is convert your dataframes to matrices
so that you are not having
...@gmail.com; r-help@r-project.org
Subject: Re: [R] avoiding loop
From: mtmor...@fhcrc.org
Date: Sun, 1 Nov 2009 22:14:09 -0800
parkbomee bbom...@hotmail.com writes:
Thank you all.
What Chuck has suggested might not be applicable since the number of
different times is around 40,000
1.7
list 9.64 1.7 9.64 1.7
exp7.12 1.2 7.12 1.2
as.data.frame.integer 5.98 1.0 8.10 1.4
To: bbom...@hotmail.com
CC: jholt...@gmail.com; r-help@r-project.org
Subject: Re: [R] avoiding loop
From
/index.html
HTH,
Chuck
CC: bbom...@hotmail.com; r-help@r-project.org
From: dwinsem...@comcast.net
To: d.rizopou...@erasmusmc.nl
Subject: Re: [R] avoiding loop
Date: Sat, 31 Oct 2009 22:26:17 -0400
This is pretty much equivalent:
tapply(DF$value[DF$choice==1], DF$time[DF$choice==1], sum
to improve my code
much.
I am using this inside of an optimization function,
and it still takes more than it needs...
CC: bbom...@hotmail.com; r-help@r-project.org
From: dwinsem...@comcast.net
To: d.rizopou...@erasmusmc.nl
Subject: Re: [R] avoiding loop
Date: Sat, 31 Oct 2009 22:26:17 -0400
...@hotmail.com; r-help@r-project.org
From: dwinsem...@comcast.net
To: d.rizopou...@erasmusmc.nl
Subject: Re: [R] avoiding loop
Date: Sat, 31 Oct 2009 22:26:17 -0400
This is pretty much equivalent:
tapply(DF$value[DF$choice==1], DF$time[DF$choice==1], sum) /
tapply(DF$value, DF$time
2009 15:35:41 -0400
Subject: Re: [R] avoiding loop
From: jholt...@gmail.com
To: bbom...@hotmail.com
CC: dwinsem...@comcast.net; d.rizopou...@erasmusmc.nl; r-help@r-project.org
What you need to do is to understand how to use Rprof so that you can
determine where the time is being spent
Hi all,
I am trying to figure out a way to improve my code's efficiency by avoiding the
use of loop.
I want to calculate a conditional mean(?) given time.
For example, from the data below, I want to calculate
sum((value|choice==1)/sum(value)) across time.
Is there a way to do it without using
one approach is the following:
# say 'DF' is your data frame, then
with(DF, {
ind - choice == 1
n - tapply(value[ind], time[ind], sum)
d - tapply(value, time, sum)
n / d
})
I hope it helps.
Best,
Dimitris
parkbomee wrote:
Hi all,
I am trying to figure out a way to improve
This is pretty much equivalent:
tapply(DF$value[DF$choice==1], DF$time[DF$choice==1], sum) /
tapply(DF$value, DF$time, sum)
And both will probably fail if the number of groups with choice==1 is
different than the number overall.
--
David.
On Oct 31, 2009, at 5:14 PM, Dimitris
...@erasmusmc.nl
Subject: Re: [R] avoiding loop
Date: Sat, 31 Oct 2009 22:26:17 -0400
This is pretty much equivalent:
tapply(DF$value[DF$choice==1], DF$time[DF$choice==1], sum) /
tapply(DF$value, DF$time, sum)
And both will probably fail if the number of groups with choice==1
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