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" )
# # # # # # # # # # # # # # # # # # # # # # # # #
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