Dear R-Experts,
Here below my reproducible example working but not entirely (working). What I
understand is that there is a problem of libraries library(hbrfit) and ... ? How
can I make it work entirely, many thanks for your precious help.
########SIMULATION STUDY 3 variables with 10% outliers n=2000
install.packages( "robustbase" )
install.packages( "MASS" )
install.packages( "quantreg" )
install.packages( "RobPer" )
install.packages("devtools")? library("devtools")
install_github("kloke/hbrfit")
install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz')
install.packages( "RobStatTM" )
library(robustbase)
library(MASS)
library(quantreg)
library(RobPer)
library(hbrfit)
library(RobStatTM)
n<-2000
x<-runif(n, 0, 5)
z <- rnorm(n, 2, 3)
a <- runif(n, 0, 5)
y_model<- 0.1*x - 0.5 * z - a + 10
y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) )
fastMM <- lmrob( y_obs ~ x+z+a)
Huber <- rlm( y_obs ~ x+z+a)
Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare )
L1 <- rq( y_obs ~ x+z+a, tau = 0.5 )
fastTau <-
FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs)
HBR<-hbrfit(y_obs ~ x+z+a)
DCML <-lmrobdetDCML(y_obs ~ x+z+a)
?
MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2)
MSE_Huber<-mean((Huber$fitted.values - y_model)^2)
MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2)
MSE_L1<-mean((L1$fitted.values - y_model)^2)
MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2)
MSE_HBR<-mean((HBR$fitted.values - y_model)^2)
MSE_DCML<-mean((DCML$fitted.values - y_model)^2)
MSE_fastMM
MSE_Huber
MSE_Tukey
MSE_L1
MSE_fastTau
MSE_HBR
MSE_DCML
###############
Hi Varin, I did not look inside your code yet but I have a few suggestions. First I think your problem should be described in more detail, just saying you have a problem is not enough for us to diagnose. Second Your example depends on too many other packages and I'm not sure if you need all of them to reproduce the error. A minimum example will be appreciated. finally, if this is a package problem as you said, it might be better to ask the question in https://github.com/kloke/hbrfit/issues since the author definitely knows the context more than us and might be able to provide a solution for your question. Best, Jiefei On Mon, Oct 21, 2019 at 12:41 PM varin sacha via R-help < r-help at r-project.org> wrote:> Dear R-Experts, > > Here below my reproducible example working but not entirely (working). > What I understand is that there is a problem of libraries library(hbrfit) > and ... ? How can I make it work entirely, many thanks for your precious > help. > > ########SIMULATION STUDY 3 variables with 10% outliers n=2000 > install.packages( "robustbase" ) > install.packages( "MASS" ) > install.packages( "quantreg" ) > install.packages( "RobPer" ) > install.packages("devtools") library("devtools") > install_github("kloke/hbrfit") install.packages(' > http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz') > install.packages( "RobStatTM" ) > > > library(robustbase) > library(MASS) > library(quantreg) > library(RobPer) > library(hbrfit) > > library(RobStatTM) > > n<-2000 > > x<-runif(n, 0, 5) > > z <- rnorm(n, 2, 3) > > a <- runif(n, 0, 5) > > y_model<- 0.1*x - 0.5 * z - a + 10 > > y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) ) > > > fastMM <- lmrob( y_obs ~ x+z+a) > > Huber <- rlm( y_obs ~ x+z+a) > > Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare ) > > L1 <- rq( y_obs ~ x+z+a, tau = 0.5 ) > > fastTau <- > FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs) > > HBR<-hbrfit(y_obs ~ x+z+a) > > DCML <-lmrobdetDCML(y_obs ~ x+z+a) > > > MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2) > > MSE_Huber<-mean((Huber$fitted.values - y_model)^2) > > MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2) > > MSE_L1<-mean((L1$fitted.values - y_model)^2) > > MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2) > > MSE_HBR<-mean((HBR$fitted.values - y_model)^2) > > MSE_DCML<-mean((DCML$fitted.values - y_model)^2) > > > MSE_fastMM > > MSE_Huber > > MSE_Tukey > > MSE_L1 > > MSE_fastTau > > MSE_HBR > > MSE_DCML > > ############### > > ______________________________________________ > 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. >[[alternative HTML version deleted]]
Hi, After I install all dependencies your example seems fine ```> MSE_fastMM[1] 2.629064e-05> > MSE_Huber[1] 1.826184e-05> > MSE_Tukey[1] 2.622499e-05> > MSE_L1[1] 1.044155e-05> > MSE_fastTau[1] NaN> > MSE_HBR[1] 1.60821e-05> > MSE_DCML[1] 9.519007e-06> > sessionInfo()R version 3.6.0 (2019-04-26) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200) Matrix products: default locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] splines stats graphics grDevices utils datasets methods base other attached packages: [1] hbrfit_0.02 Rfit_0.23.0 RobStatTM_1.0.1 fit.models_0.5-14 [5] RobPer_1.2.2 rgenoud_5.8-3.0 BB_2019.10-1 quantreg_5.51 [9] SparseM_1.77 MASS_7.3-51.4 robustbase_0.93-5 ``` There is no error or warning, except that MSE_fastTau is an NaN. What problem are you looking for? Best, Jiefei On Mon, Oct 21, 2019 at 12:41 PM varin sacha via R-help < r-help at r-project.org> wrote:> Dear R-Experts, > > Here below my reproducible example working but not entirely (working). > What I understand is that there is a problem of libraries library(hbrfit) > and ... ? How can I make it work entirely, many thanks for your precious > help. > > ########SIMULATION STUDY 3 variables with 10% outliers n=2000 > install.packages( "robustbase" ) > install.packages( "MASS" ) > install.packages( "quantreg" ) > install.packages( "RobPer" ) > install.packages("devtools") library("devtools") > install_github("kloke/hbrfit") install.packages(' > http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz') > install.packages( "RobStatTM" ) > > > library(robustbase) > library(MASS) > library(quantreg) > library(RobPer) > library(hbrfit) > > library(RobStatTM) > > n<-2000 > > x<-runif(n, 0, 5) > > z <- rnorm(n, 2, 3) > > a <- runif(n, 0, 5) > > y_model<- 0.1*x - 0.5 * z - a + 10 > > y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) ) > > > fastMM <- lmrob( y_obs ~ x+z+a) > > Huber <- rlm( y_obs ~ x+z+a) > > Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare ) > > L1 <- rq( y_obs ~ x+z+a, tau = 0.5 ) > > fastTau <- > FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs) > > HBR<-hbrfit(y_obs ~ x+z+a) > > DCML <-lmrobdetDCML(y_obs ~ x+z+a) > > > MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2) > > MSE_Huber<-mean((Huber$fitted.values - y_model)^2) > > MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2) > > MSE_L1<-mean((L1$fitted.values - y_model)^2) > > MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2) > > MSE_HBR<-mean((HBR$fitted.values - y_model)^2) > > MSE_DCML<-mean((DCML$fitted.values - y_model)^2) > > > MSE_fastMM > > MSE_Huber > > MSE_Tukey > > MSE_L1 > > MSE_fastTau > > MSE_HBR > > MSE_DCML > > ############### > > ______________________________________________ > 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. >[[alternative HTML version deleted]]
Dear Wang,
Really appreciated but I have tried dependencies=TRUE and it still does not
work.
Is it because my R version is 3.6.1 ? sessionInfo() at the end of the message
install.packages( "robustbase",dependencies=TRUE )
install.packages( "MASS" ,dependencies=TRUE )
install.packages( "quantreg" ,dependencies=TRUE )
install.packages( "RobPer",dependencies=TRUE ?)
install.packages("devtools",dependencies=TRUE )?
install_github("kloke/hbrfit",dependencies=TRUE)
install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz',dependencies=TRUE
)
install.packages( "RobStatTM",dependencies=TRUE ?)
library(robustbase)
library(MASS)
library(quantreg)
library(RobPer)
library(hbrfit)
library(RobStatTM)
sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6
Matrix products: default
BLAS:??
/Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK:
/Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
Random number generation:
RNG:???? Mersenne-Twister?
Normal:? Inversion?
Sample:? Rounding?
locale:[1] fr_CH.UTF-8/fr_CH.UTF-8/fr_CH.UTF-8/C/fr_CH.UTF-8/fr_CH.UTF-8
attached base packages:[1] stats???? graphics? grDevices utils???? datasets?
methods?? base????
loaded via a namespace (and not attached):[1] compiler_3.6.1
Le lundi 21 octobre 2019 ? 20:12:02 UTC+2, Wang Jiefei <szwjf08 at
gmail.com> a ?crit :
Hi,
After I install all dependencies your example seems fine
```> MSE_fastMM
[1] 2.629064e-05>
> MSE_Huber
[1] 1.826184e-05>
> MSE_Tukey
[1] 2.622499e-05>
> MSE_L1
[1] 1.044155e-05>
> MSE_fastTau
[1] NaN>
> MSE_HBR
[1] 1.60821e-05>
> MSE_DCML
[1] 9.519007e-06>
> sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 ?LC_CTYPE=English_United States.1252 ?
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C ? ? ? ? ? ? ? ? ? ? ? ?
?
[5] LC_TIME=English_United States.1252 ? ?
attached base packages:
[1] splines ? stats ? ? graphics ?grDevices utils ? ? datasets ?methods ? base ?
?
other attached packages:
?[1] hbrfit_0.02 ? ? ? Rfit_0.23.0 ? ? ? RobStatTM_1.0.1 ? fit.models_0.5-14
?[5] RobPer_1.2.2 ? ? ?rgenoud_5.8-3.0 ? BB_2019.10-1 ? ? ?quantreg_5.51 ? ?
?[9] SparseM_1.77 ? ? ?MASS_7.3-51.4 ? ? robustbase_0.93-5
```
There is no error or warning, except that? MSE_fastTau is an NaN. What
problem?are you looking for?
Best,
Jiefei
On Mon, Oct 21, 2019 at 12:41 PM varin sacha via R-help <r-help at
r-project.org> wrote:> Dear R-Experts,
>
> Here below my reproducible example working but not entirely (working). What
I understand is that there is a problem of libraries library(hbrfit) and ... ?
How can I make it work entirely, many thanks for your precious help.
>
> ########SIMULATION STUDY 3 variables with 10% outliers n=2000
> install.packages( "robustbase" )
> install.packages( "MASS" )
> install.packages( "quantreg" )
> install.packages( "RobPer" )
> install.packages("devtools")? library("devtools")
install_github("kloke/hbrfit")
install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz')
> install.packages( "RobStatTM" )
>
>
> library(robustbase)
> library(MASS)
> library(quantreg)
> library(RobPer)
> library(hbrfit)
>
> library(RobStatTM)
>
> n<-2000
>
> x<-runif(n, 0, 5)
>
> z <- rnorm(n, 2, 3)
>
> a <- runif(n, 0, 5)
>
> y_model<- 0.1*x - 0.5 * z - a + 10
>
> y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) )
>
>
> fastMM <- lmrob( y_obs ~ x+z+a)
>
> Huber <- rlm( y_obs ~ x+z+a)
>
> Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare )
>
> L1 <- rq( y_obs ~ x+z+a, tau = 0.5 )
>
> fastTau <-
FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs)
>
> HBR<-hbrfit(y_obs ~ x+z+a)
>
> DCML <-lmrobdetDCML(y_obs ~ x+z+a)
>
> ?
> MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2)
>
> MSE_Huber<-mean((Huber$fitted.values - y_model)^2)
>
> MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2)
>
> MSE_L1<-mean((L1$fitted.values - y_model)^2)
>
> MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2)
>
> MSE_HBR<-mean((HBR$fitted.values - y_model)^2)
>
> MSE_DCML<-mean((DCML$fitted.values - y_model)^2)
>
>
> MSE_fastMM
>
> MSE_Huber
>
> MSE_Tukey
>
> MSE_L1
>
> MSE_fastTau
>
> MSE_HBR
>
> MSE_DCML
>
> ###############
>
> ______________________________________________
> 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.
>
On 10/21/19 9:40 AM, varin sacha via R-help wrote:> Dear R-Experts, > > Here below my reproducible example working but not entirely (working). What I understand is that there is a problem of libraries library(hbrfit) and ... ? How can I make it work entirely, many thanks for your precious help. > > ########SIMULATION STUDY 3 variables with 10% outliers n=2000 > install.packages( "robustbase" ) > install.packages( "MASS" ) > install.packages( "quantreg" ) > install.packages( "RobPer" ) > install.packages("devtools")? library("devtools") install_github("kloke/hbrfit")When I attempted to replicate your code, I deciced to issue both of these commands in hte line above on separate lines. If you entered as above there shoiuld have been an error because there needs to be a semicolon to separate more than one? distinct command on a single line.> install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz') > install.packages( "RobStatTM" ) > > > library(robustbase) > library(MASS) > library(quantreg) > library(RobPer) > library(hbrfit) > > library(RobStatTM) > > n<-2000 > > x<-runif(n, 0, 5) > > z <- rnorm(n, 2, 3) > > a <- runif(n, 0, 5) > > y_model<- 0.1*x - 0.5 * z - a + 10 > > y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) ) > > > fastMM <- lmrob( y_obs ~ x+z+a) > > Huber <- rlm( y_obs ~ x+z+a) > > Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare ) > > L1 <- rq( y_obs ~ x+z+a, tau = 0.5 ) > > fastTau <- FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs)At this point the compiler should emit an error since newdata has not been created: fastTau <- FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs) Error in eval(predvars, data, env) : object 'newdata' not found ?-- David.> > HBR<-hbrfit(y_obs ~ x+z+a) > > DCML <-lmrobdetDCML(y_obs ~ x+z+a) > > > MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2) > > MSE_Huber<-mean((Huber$fitted.values - y_model)^2) > > MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2) > > MSE_L1<-mean((L1$fitted.values - y_model)^2) > > MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2) > > MSE_HBR<-mean((HBR$fitted.values - y_model)^2) > > MSE_DCML<-mean((DCML$fitted.values - y_model)^2) > > > MSE_fastMM > > MSE_Huber > > MSE_Tukey > > MSE_L1 > > MSE_fastTau > > MSE_HBR > > MSE_DCML > > ############### > > ______________________________________________ > 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.
Dear David, Dear Jiefei,
Many thanks for your comments. I got it now. It works.
Best,
Sacha
Le lundi 21 octobre 2019 ? 22:00:39 UTC+2, David Winsemius <dwinsemius at
comcast.net> a ?crit :
On 10/21/19 9:40 AM, varin sacha via R-help wrote:> Dear R-Experts,
>
> Here below my reproducible example working but not entirely (working). What
I understand is that there is a problem of libraries library(hbrfit) and ... ?
How can I make it work entirely, many thanks for your precious help.
>
> ########SIMULATION STUDY 3 variables with 10% outliers n=2000
> install.packages( "robustbase" )
> install.packages( "MASS" )
> install.packages( "quantreg" )
> install.packages( "RobPer" )
> install.packages("devtools")? library("devtools")
install_github("kloke/hbrfit")
When I attempted to replicate your code, I deciced to issue both of
these commands in hte line above on separate lines. If you entered as
above there shoiuld have been an error because there needs to be a
semicolon to separate more than one? distinct command on a single line.
>
install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz')
> install.packages( "RobStatTM" )
>
>
> library(robustbase)
> library(MASS)
> library(quantreg)
> library(RobPer)
> library(hbrfit)
>
> library(RobStatTM)
>
> n<-2000
>
> x<-runif(n, 0, 5)
>
> z <- rnorm(n, 2, 3)
>
> a <- runif(n, 0, 5)
>
> y_model<- 0.1*x - 0.5 * z - a + 10
>
> y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) )
>
>
> fastMM <- lmrob( y_obs ~ x+z+a)
>
> Huber <- rlm( y_obs ~ x+z+a)
>
> Tukey <- rlm( y_obs ~ x+z+a, psi = psi.bisquare )
>
> L1 <- rq( y_obs ~ x+z+a, tau = 0.5 )
>
> fastTau <-
FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs)
At this point the compiler should emit an error since newdata has not
been created:
fastTau <-
FastTau(model.matrix(~newdata$x+newdata$z+newdata$a),newdata$y_obs)
Error in eval(predvars, data, env) : object 'newdata' not found
?--
David.
>
> HBR<-hbrfit(y_obs ~ x+z+a)
>
> DCML <-lmrobdetDCML(y_obs ~ x+z+a)
>
>?
> MSE_fastMM<-mean((fastMM$fitted.values - y_model)^2)
>
> MSE_Huber<-mean((Huber$fitted.values - y_model)^2)
>
> MSE_Tukey<-mean((Tukey$fitted.values - y_model)^2)
>
> MSE_L1<-mean((L1$fitted.values - y_model)^2)
>
> MSE_fastTau<-mean((fastTau$fitted.values - y_model)^2)
>
> MSE_HBR<-mean((HBR$fitted.values - y_model)^2)
>
> MSE_DCML<-mean((DCML$fitted.values - y_model)^2)
>
>
> MSE_fastMM
>
> MSE_Huber
>
> MSE_Tukey
>
> MSE_L1
>
> MSE_fastTau
>
> MSE_HBR
>
> MSE_DCML
>
> ###############
>
> ______________________________________________
> 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.
[[alternative HTML version deleted]]