# Simulations study not working entirely...

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## Simulations study not working entirely...

 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 ############### ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Simulations study not working entirely...

 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 < [hidden email]> 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 > > ############### > > ______________________________________________ > [hidden email] 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]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Simulations study not working entirely...

 In reply to this post by R help mailing list-2 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 < [hidden email]> 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 > > ############### > > ______________________________________________ > [hidden email] 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]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Simulations study not working entirely...

 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 <[hidden email]> 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 <[hidden email]> 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 > > ############### > > ______________________________________________ > [hidden email] 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. > ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Simulations study not working entirely...

 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 <[hidden email]> 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 <[hidden email]> > 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 < > [hidden email]> 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 > > > > ############### > > > > ______________________________________________ > > [hidden email] 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]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.