[R] Simulations study not working entirely...

[Wang Jiefei]

What problem you have encountered? I still do not know your question.
Please elaborate on your question and post the error message or
something else that prevents you from running the code.

Thanks,
Jiefei

On Mon, Oct 21, 2019 at 3:13 PM varin sacha <varinsacha using yahoo.fr> wrote:

>  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 à 20:12:02 UTC+2, Wang Jiefei <szwjf08 using gmail.com>
> a écrit :
>
>
>
>
>
> 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 using 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 using 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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