[R] Same results but different functions ?

[varin sacha]

Dear R-experts,

The rlm command in the MASS package command implements several versions of robust regression, for example the Huber and the Tukey (bisquare weighting function) estimators.
In my R code here below I try to get the Tukey (bisquare weighting function) estimation, R gives me an error message : Error in statistic(data, original, ...) : unused argument (psi = psi.bisquare)
If I cancel psi=psi.bisquare my code is working but IMHO I will get the Huber estimation and not the Tukey. So how can I get the Tukey ? Many thanks for your help.


# # # # # # # # # # # # # # # # # # # # # # # #
install.packages( "boot",dependencies=TRUE )
install.packages( "MASS",dependencies=TRUE  )
library(boot)
library(MASS)

n<-50
b<-runif(n, 0, 5)
z <- rnorm(n, 2, 3)
a <- runif(n, 0, 5)

y_model<- 0.1*b - 0.5 * z - a + 10
y_obs <- y_model +c( rnorm(n*0.9, 0, 0.1), rnorm(n*0.1, 0, 0.5) )
df<-data.frame(b,z,a,y_obs)

 # function to obtain MSE
 MSE <- function(data, indices, formula) {
    d <- data[indices, ] # allows boot to select sample
    fit <- rlm(formula, data = d)
    ypred <- predict(fit)
    d[["y_obs "]] <-y_obs
    mean((d[["y_obs"]]-ypred)^2)
 }

 # Make the results reproducible
 set.seed(1234)
 
 # bootstrapping with 600 replications
 results <- boot(data = df, statistic = MSE,
                  R = 600, formula = y_obs ~ b+z+a, psi = psi.bisquare)

str(results)

boot.ci(results, type="bca" )
# # # # # # # # # # # # # # # # # # # # # # # # #