Dear R-helpers,
Using the HBR (high breakdown rank-based) robust estimator and the hbrfit
function, I get an error saying Error in UseMethod("predict") for hbrfit. How
can I solve the problem ? Many thanks for your help.
# # # # # # # # # # # # # # # # # # # # # # # #
install.packages( "robustbase",dependencies=TRUE )
install.packages( "boot",dependencies=TRUE )
install.packages( "MASS",dependencies=TRUE )
install.packages( "quantreg",dependencies=TRUE )
install.packages( "RobPer",dependencies=TRUE )
install_github("kloke/hbrfit")
install.packages('http://www.stat.wmich.edu/mckean/Stat666/Pkgs/npsmReg2_0.1.1.tar.gz')
install.packages( "RobStatTM",dependencies=TRUE )
library(boot)
library(robustbase)
library(MASS)
library(quantreg)
library(RobPer)
library(hbrfit)
library(RobStatTM)
n<-200
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 <- hbrfit(formula, data = d)
ypred <- predict(fit)
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)
str(results)
boot.ci(results, type="bca" )
# # # # # # # # # # # # # # # # # # # # # # # # #
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