The documentation suggests that the rlm method for a formula does not have psi as a parameter. Perhaps try using the method for a matrix x and a vector y.

Michael

On 23/03/2020 12:39, varin sacha via R-help wrote:
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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--
Michael
http://www.dewey.myzen.co.uk/home.html

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