[R] Bootstrapped CIs of MSE for (G)AM model

[Rui Barradas]

Hello,

Sorry, there's a close parenthesis too many in the call to boot, the 
very last one.
Delete it and it runs with no errors.

Rui Barradas

Às 21:55 de 22/11/2018, Rui Barradas escreveu:
> Hello,
> 
> There were several errors with your code. The following works but with 
> the other CI types.
> 
> 
> library(ISLR)
> library(mgcv)
> library(boot)
> 
> # function to obtain MSE
> MSE <- function(data, indices, formula) {
>    d <- data[indices, ] # allows boot to select sample
>    fit <- gam(formula, data = d)
>    ypred <- predict(fit)
>    mean((d[["wage"]] - ypred)^2)
> }
> 
> data(Wage)
> 
> # Make the results reproducible
> set.seed(1234)
> 
> # bootstrapping with 1000 replications
> results <- boot(data = Wage, statistic = MSE,
>                  R = 1000, formula = wage ~ education + s(age, bs = 
> "ps") + year))
> 
> # get 95% confidence intervals
> # type = "bca" is throwing an error
> ci.type <- c("norm","basic", "stud", "perc")
> boot.ci(results, type = ci.type)
> 
> 
> 
> Hope this helps,
> 
> Rui Barradas
> 
> Às 20:36 de 22/11/2018, varin sacha via R-help escreveu:
>> Dear R-experts,
>>
>> I am trying to get the bootstrapped confidence intervals of Mean 
>> squared error (MSE) for a (G)AM model. I get an error message.
>> Here below the reproducible R code. Many thanks for your response.
>>
>> ####################
>>
>>
>> install.packages("ISLR")
>>
>> library(ISLR)
>>
>> install.packages("mgcv")
>>
>> library(mgcv)
>>
>> install.packages("boot")
>>
>> library(boot)
>>
>> #MSE calculation
>>
>> n=dim(Wage)[1]
>>
>> p=0.667
>>
>> GAM1<-gam(wage ~education+s(age,bs="ps")+year,data=Wage)
>>
>> sam=sample(1 :n,floor(p*n),replace=FALSE)
>>
>>
>> Training =Wage [sam,]
>>
>> Testing = Wage [-sam,]
>>
>>
>> ypred=predict(GAM1,newdata=Testing)
>>
>> y=Testing$wage
>>
>> MSE = mean((y-ypred)^2)
>>
>>
>> # Bootstrap 95% CI for MSE
>>
>> # function to obtain MSE
>> MSE <- function(formula, data, indices) {
>>    d <- data[indices,] # allows boot to select sample
>>    fit <- gam(formula, data=d)
>>    return(MSE(fit))
>>
>> } # bootstrapping with 1000 replications
>> results <- boot(data=Wage, statistic=MSE,
>>     R=1000, formula=gam(wage ~education+s(age,bs="ps")+year,data=Wage)
>>
>> )
>> # get 95% confidence intervals
>> boot.ci(results, type="bca")
>>
>> ##########################
>>
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide 
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.