R help - Jun 2005 - errorest

Hi,

I am using errorest function from ipred package.
I am hoping to perform "bootstrap 0.632+" and "bootstrap leave
one out".
According to the manual page for errorest, i use the following command:

ce632[i]<-errorest(ytrain ~., data=mydata, model=lda, 
estimator=c("boot","632plus"),  predict=mypredict.lda)$error

It didn't work. I then tried the following two commands:

ce632[i]<-errorest(ytrain ~., data=mydata, model=lda, 
estimator=c("632plus"), est.para=control.errorest(nboot=B), 
predict=mypredict.lda)$error

ceLOOB[i]<-errorest(ytrain ~., data=mydata, model=lda,
estimator=c("cv"),
est.para=control.errorest(k=cv.k,nboot=B), predict=mypredict.lda)$error

They worked. However, as I didn't specify "boot" in estimator, I
am
wondering if "bootstrap" is still perfomred. I set nboot=B in
est.para.

Thanks in advance.

Jenny

Jenny,

"It didn't work" and "They worked" aren't very
specific. Also, the package
name is ipred and the function is errorest.

The estimator entry on the man page for errorest has:

   'cv' cross-validation, 'boot' bootstrap or '632plus'
bias corrected
bootstrap (classification only). 

Note the *or*. I tried the analysis of the iris data from the man page with
your estimator specification:
> testing <-   errorest(Species ~ ., data=iris, model=lda, 
+ estimator = c("boot","632plus"), predict=
mypredict.lda)
> testing
Call:
errorest.data.frame(formula = Species ~ ., data = iris, model = lda, 
    predict = mypredict.lda, estimator = c("boot",
"632plus"))

         Bootstrap estimator of misclassification error 
         with 25 bootstrap replications

Misclassification error:  0.0235 
Standard deviation: 0.0028 


Call:
errorest.data.frame(formula = Species ~ ., data = iris, model = lda, 
    predict = mypredict.lda, estimator = c("boot",
"632plus"))

         .632+ Bootstrap estimator of misclassification error 
         with 25 bootstrap replications

Misclassification error:  0.0222 
>               
> unclass(testing)
$boot
$boot$error
[1] 0.02351852

$boot$sd
[1] 0.002847447

$boot$bc632plus
[1] FALSE

$boot$nboot
[1] 25


$"632plus"
$"632plus"$error
[1] 0.02222817

$"632plus"$nboot
[1] 25

$"632plus"$bc632plus
[1] TRUE


$call
errorest.data.frame(formula = Species ~ ., data = iris, model = lda, 
    predict = mypredict.lda, estimator = c("boot",
"632plus"))

Is this consistent with your results?

Max


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