[R] No predict method for hbrfit

[Jeff Newmiller]

Don't use packages that haven't been maintained. Or correspond with the author. Or, fix them yourself.

On March 21, 2020 4:09:13 PM PDT, varin sacha via R-help <r-help using r-project.org> wrote:
>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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-- 
Sent from my phone. Please excuse my brevity.