[R] Confidence intervals around the MIC (Maximal information coefficient)
Dear R-Experts,
Here below is my R code (reproducible example) to calculate the confidence
intervals around the spearman coefficient.
##
C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
cor(C,D,method= "spearman")
library(boot)
myCor=function(data,index){
cor(data[index, ])[1,2]
}
results=boot(data=cbind(C,D),statistic=myCor, R=2000)
boot.ci(results,type="all")
##
Now, I would like to calculate the CIs around the MIC (Maximal information
coefficient). The MIC can be calculated thanks to the library(minerva). I don’t
get the CIs for the MIC, I don’t know how to change my R codes to get the CIs
around the MIC. Any help would be highly appreciated :
##
library(minerva)
mine(C,D)
library(boot)
myCor=function(data,index){
mic(data[index, ])[1,2]
}
results=boot(data=cbind(C,D),statistic=myCor, R=2000)
boot.ci(results,type="all")
##
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Re: [R] Confidence intervals around the MIC (Maximal information coefficient)
Hello,
First of all, when I tried to use function mic I got an error.
mic(cbind(C, D))
Error in mic(cbind(C, D)) : could not find function "mic"
So I've changed your function myCor and all went well, with a warning
relative to BCa intervals.
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Hope this helps,
Rui Barradas
On 12/10/2017 3:19 PM, varin sacha via R-help wrote:
Dear R-Experts,
Here below is my R code (reproducible example) to calculate the confidence
intervals around the spearman coefficient.
##
C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
cor(C,D,method= "spearman")
library(boot)
myCor=function(data,index){
cor(data[index, ])[1,2]
}
results=boot(data=cbind(C,D),statistic=myCor, R=2000)
boot.ci(results,type="all")
##
Now, I would like to calculate the CIs around the MIC (Maximal information
coefficient). The MIC can be calculated thanks to the library(minerva). I don’t
get the CIs for the MIC, I don’t know how to change my R codes to get the CIs
around the MIC. Any help would be highly appreciated :
##
library(minerva)
mine(C,D)
library(boot)
myCor=function(data,index){
mic(data[index, ])[1,2]
}
results=boot(data=cbind(C,D),statistic=myCor, R=2000)
boot.ci(results,type="all")
##
__
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and provide commented, minimal, self-contained, reproducible code.
__
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Re: [R] Confidence intervals around the MIC (Maximal information coefficient)
Hi Rui,
Many thanks. The R code works BUT the results I get are quite weird I guess !
MIC = 0.2650
Normal 95% CI = (0.9614, 1.0398)
The MIC is not inside the confidence intervals !
Is there something wrong in the R code ?
Here is the reproducible example :
##
C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
library(minerva)
mine(C,D)$MIC
library(boot)
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
##
De : Rui Barradas
roject.org>
Envoyé le : Dimanche 10 décembre 2017 16h34
Objet : Re: [R] Confidence intervals around the MIC (Maximal information
coefficient)
Hello,
First of all, when I tried to use function mic I got an error.
mic(cbind(C, D))
Error in mic(cbind(C, D)) : could not find function "mic"
So I've changed your function myCor and all went well, with a warning
relative to BCa intervals.
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Hope this helps,
Rui Barradas
On 12/10/2017 3:19 PM, varin sacha via R-help wrote:
> Dear R-Experts,
>
> Here below is my R code (reproducible example) to calculate the confidence
> intervals around the spearman coefficient.
>
> ##
> C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
> D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
> cor(C,D,method= "spearman")
> library(boot)
> myCor=function(data,index){
> cor(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
>
> Now, I would like to calculate the CIs around the MIC (Maximal information
> coefficient). The MIC can be calculated thanks to the library(minerva). I
> don’t get the CIs for the MIC, I don’t know how to change my R codes to get
> the CIs around the MIC. Any help would be highly appreciated :
>
> ##
> library(minerva)
> mine(C,D)
> library(boot)
> myCor=function(data,index){
> mic(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Confidence intervals around the MIC (Maximal information coefficient)
You need:
myCor <- function(data, index){
mine(data[index, ])$MIC[1, 2]
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Look at the differences between:
mine(C, D)
and
mine(cbind(C, D))
The first returns a value, the second returns a symmetric matrix. Just like
cor()
David L. Carlson
Department of Anthropology
Texas A&M University
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of varin sacha via
R-help
Sent: Sunday, December 10, 2017 11:07 AM
To: Rui Barradas ; R-help Mailing List
Subject: Re: [R] Confidence intervals around the MIC (Maximal information
coefficient)
Hi Rui,
Many thanks. The R code works BUT the results I get are quite weird I guess !
MIC = 0.2650
Normal 95% CI = (0.9614, 1.0398)
The MIC is not inside the confidence intervals !
Is there something wrong in the R code ?
Here is the reproducible example :
##
C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
library(minerva)
mine(C,D)$MIC
library(boot)
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
##
De : Rui Barradas
roject.org>
Envoyé le : Dimanche 10 décembre 2017 16h34
Objet : Re: [R] Confidence intervals around the MIC (Maximal information
coefficient)
Hello,
First of all, when I tried to use function mic I got an error.
mic(cbind(C, D))
Error in mic(cbind(C, D)) : could not find function "mic"
So I've changed your function myCor and all went well, with a warning
relative to BCa intervals.
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Hope this helps,
Rui Barradas
On 12/10/2017 3:19 PM, varin sacha via R-help wrote:
> Dear R-Experts,
>
> Here below is my R code (reproducible example) to calculate the confidence
> intervals around the spearman coefficient.
>
> ##
> C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
> D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
> cor(C,D,method= "spearman")
> library(boot)
> myCor=function(data,index){
> cor(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
>
> Now, I would like to calculate the CIs around the MIC (Maximal information
> coefficient). The MIC can be calculated thanks to the library(minerva). I
> don’t get the CIs for the MIC, I don’t know how to change my R codes to get
> the CIs around the MIC. Any help would be highly appreciated :
>
> ##
> library(minerva)
> mine(C,D)
> library(boot)
> myCor=function(data,index){
> mic(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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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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.
Re: [R] MSVAR model
> On Dec 9, 2017, at 8:51 PM, ah a via R-help wrote:
>
> Hello,
>
> As I'm interested to search about the monetary transmission channel in our
> country by MSVAR model,Could you do me favor and tell me How I can run
> different types of MSVAR model (such as MSIAH(2)-VAR(2)) and finding
> impulse response function in different regimes and also variance
> decomposition?
This is uncomfortably close to an existing fortune:
fortunes::fortune("brain surgery")
Why don't you read the Posting Guide. Then perhaps you can improve your
question?
--
David.
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
__
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Re: [R] Confidence intervals around the MIC (Maximal information coefficient)
Hi David, Rui,
Thanks for your precious responses. It works !
Best,
De : David L Carlson
.pt>
Cc : "r-help@r-project.org"
Envoyé le : Dimanche 10 décembre 2017 19h05
Objet : RE: [R] Confidence intervals around the MIC (Maximal information
coefficient)
You need:
myCor <- function(data, index){
mine(data[index, ])$MIC[1, 2]
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Look at the differences between:
mine(C, D)
and
mine(cbind(C, D))
The first returns a value, the second returns a symmetric matrix. Just like
cor()
David L. Carlson
Department of Anthropology
Texas A&M University
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of varin sacha via
R-help
Sent: Sunday, December 10, 2017 11:07 AM
To: Rui Barradas ; R-help Mailing List
Subject: Re: [R] Confidence intervals around the MIC (Maximal information
coefficient)
Hi Rui,
Many thanks. The R code works BUT the results I get are quite weird I guess !
MIC = 0.2650
Normal 95% CI = (0.9614, 1.0398)
[[elided Yahoo spam]]
Is there something wrong in the R code ?
Here is the reproducible example :
##
C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
library(minerva)
mine(C,D)$MIC
library(boot)
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
##
De : Rui Barradas
roject.org>
Envoyé le : Dimanche 10 décembre 2017 16h34
Objet : Re: [R] Confidence intervals around the MIC (Maximal information
coefficient)
Hello,
First of all, when I tried to use function mic I got an error.
mic(cbind(C, D))
Error in mic(cbind(C, D)) : could not find function "mic"
So I've changed your function myCor and all went well, with a warning
relative to BCa intervals.
myCor <- function(data, index){
mine(data[index, ])$MIC
}
results=boot(data = cbind(C,D), statistic = myCor, R = 2000)
boot.ci(results,type="all")
Hope this helps,
Rui Barradas
On 12/10/2017 3:19 PM, varin sacha via R-help wrote:
> Dear R-Experts,
>
> Here below is my R code (reproducible example) to calculate the confidence
> intervals around the spearman coefficient.
>
> ##
> C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2)
> D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9)
> cor(C,D,method= "spearman")
> library(boot)
> myCor=function(data,index){
> cor(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
>
> Now, I would like to calculate the CIs around the MIC (Maximal information
> coefficient). The MIC can be calculated thanks to the library(minerva). I
> don’t get the CIs for the MIC, I don’t know how to change my R codes to get
> the CIs around the MIC. Any help would be highly appreciated :
>
> ##
> library(minerva)
> mine(C,D)
> library(boot)
> myCor=function(data,index){
> mic(data[index, ])[1,2]
> }
> results=boot(data=cbind(C,D),statistic=myCor, R=2000)
> boot.ci(results,type="all")
> ##
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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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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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] file creating
I am using R(3.4.3), Win 7(extreme edition) 32 bit, I have 10 excel files data1,xls, data2.xls .. till data10.xls. I want to create 10 dataframes . How to do ? regards Parth [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
Re: [R] file creating
You could loop over the file names, read each excel file and store the
individual data frames in a list using lapply.
I prefer to read excel files with the package readxl.
The code could be along the lines of
library(readxl)
my_files <- c("file1", "file2")
lapply(my_files, read_excel)
HTH
Ulrik
Partha Sinha schrieb am Mo., 11. Dez. 2017, 08:13:
> I am using R(3.4.3), Win 7(extreme edition) 32 bit,
> I have 10 excel files data1,xls, data2.xls .. till data10.xls.
> I want to create 10 dataframes . How to do ?
> regards
> Parth
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
[[alternative HTML version deleted]]
__
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