[R] Simulations study not working entirely...

[varin sacha]

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

###############