varin sacha
2017-Dec-10 17:07 UTC
[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 <ruipbarradas at sapo.pt> roject.org> Envoy? le : Dimanche 10 d?cembre 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, ])$MIC } results=boot(data = cbind(C,D), statistic = myCor, R = 2000) boot.ci(results,type="all") Hope this helps, Rui Barradas On 12/10/2017 3:19 PM, varin sacha via R-help wrote:> Dear R-Experts, > > Here below is my R code (reproducible example) to calculate the confidence intervals around the spearman coefficient. > > ########## > C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2) > D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9) > cor(C,D,method= "spearman") > library(boot) > myCor=function(data,index){ > cor(data[index, ])[1,2] > } > results=boot(data=cbind(C,D),statistic=myCor, R=2000) > boot.ci(results,type="all") > ########## > > > Now, I would like to calculate the CIs around the MIC (Maximal information coefficient). The MIC can be calculated thanks to the library(minerva). I don?t get the CIs for the MIC, I don?t know how to change my R codes to get the CIs around the MIC. Any help would be highly appreciated : > > ########## > library(minerva) > mine(C,D) > library(boot) > myCor=function(data,index){ > mic(data[index, ])[1,2] > } > results=boot(data=cbind(C,D),statistic=myCor, R=2000) > boot.ci(results,type="all") > ########## > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
David L Carlson
2017-Dec-10 18:04 UTC
[R] Confidence intervals around the MIC (Maximal information coefficient)
You need: myCor <- function(data, index){ mine(data[index, ])$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-bounces at r-project.org] On Behalf Of varin sacha via R-help Sent: Sunday, December 10, 2017 11:07 AM To: Rui Barradas <ruipbarradas at sapo.pt>; R-help Mailing List <r-help at r-project.org> 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 <ruipbarradas at sapo.pt> roject.org> Envoy? le : Dimanche 10 d?cembre 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 at 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 at 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.
varin sacha
2017-Dec-10 19:55 UTC
[R] Confidence intervals around the MIC (Maximal information coefficient)
Hi David, Rui, Thanks for your precious responses. It works ! Best, ________________________________ De : David L Carlson <dcarlson at tamu.edu> .pt> Cc : "r-help at r-project.org" <r-help at r-project.org> Envoy? le : Dimanche 10 d?cembre 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-bounces at r-project.org] On Behalf Of varin sacha via R-help Sent: Sunday, December 10, 2017 11:07 AM To: Rui Barradas <ruipbarradas at sapo.pt>; R-help Mailing List <r-help at r-project.org> 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 <ruipbarradas at sapo.pt> roject.org> Envoy? le : Dimanche 10 d?cembre 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 at 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 at 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.