# [R] Bootstrapped Regression

Janh Anni annijanh at gmail.com
Mon Oct 16 03:01:47 CEST 2017

```Hello Rui,

It was perfect!  Thank you so much for your kindness.  It is greatly
appreciated.

All the best,
Janh

On Sun, Oct 15, 2017 at 3:25 AM, Rui Barradas <ruipbarradas at sapo.pt> wrote:

> Hello,
>
> Much clearer now, thanks.
> It's a matter of changing the function boot calls to return the predicted
> values at the point of interess, education = 50, income = 75.
>
> I have changed the way the function uses the indices a bit, the result is
> the same, it's just the way I usually do it.
>
> pred.duncan.function <- function(data, indices) {
>     mod <- lm(prestige ~ education + income, data = data[indices, ])
>     new <- data.frame(education = 50, income = 75)
>     predict(mod, newdata = new)
> }
>
> set.seed(94)    # make the results reproducible
>
> Predicted <- boot(Duncan, pred.duncan.function , 1000)
> Predicted\$t0
> boot.ci(Predicted, index = 1, conf = 0.95, type=c("basic", "norm",
> "perc", "bca"))
>
>
> Hope this helps,
>
>
> Em 15-10-2017 02:22, Janh Anni escreveu:
>
>> Hello Rui,
>>
>> Thanks for your helpful suggestions.  Just for illustration, let's use the
>> well known Duncan dataset of prestige vs education + income that is
>> contained in the "car" package.  Suppose I wish to use boot function to
>> bootstrap a linear regression of prestige ~ education + income and use the
>> following script:
>>
>> duncan.function <- function(data, indices) {data = data[indices,]
>>
>> mod <- lm(prestige ~ education + income, data=data,)
>>
>> coefficients(mod)}
>>
>> Results <- boot(Duncan, duncan.function , 1000)
>> Results
>>
>> So the 1000 bootstrapped coefficients are contained in Results and I can
>> use the boot.ci function in the same boot package to obtain the
>> confidence
>> intervals for the, say, education coefficient with something like:
>>
>> boot.ci(Results, index=2, conf = 0.95, type=c("basic", "norm", "perc",
>> "bca"))
>>
>> Then, suppose I am interested in getting a confidence interval for the
>> predicted  prestige at, say, education = 50 and income = 75.  The question
>> is how do I get boot to compute 1000 values of the predicted prestige at
>> education = 50 and income = 75, so that I can subsequently (hopefully)
>> have
>> boot.ci compute the confidence intervals as it did for the bootstrapped
>> coefficients? As for prediction intervals, it wouldn't seem conceptually
>> feasible in this context?  Thanks again for all your help.
>>
>> Janh
>>
>> On Sat, Oct 14, 2017 at 11:12 AM, Bert Gunter <bgunter.4567 at gmail.com>
>> wrote:
>>
>> R-help is not a free coding service. We expect users to make the effort to
>>> learn R and *may* provide help when they get stuck. Pay a local R
>>> programmer if you do not wish to make such an effort.
>>>
>>> Cheers,
>>> Bert
>>>
>>>
>>> On Oct 14, 2017 7:58 AM, "Janh Anni" <annijanh at gmail.com> wrote:
>>>
>>> Greetings!
>>>
>>> We are trying to obtain confidence and prediction intervals for a
>>> predicted
>>> Y value from bootstrapped linear regression using the boot function. Does
>>> anyone know how to code it?  Greatly appreciated.
>>>
>>> Janh
>>>
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>>>
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>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> ng-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>

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```