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)
head(Predicted)
Predicted$t0
boot.ci(Predicted, index = 1, conf = 0.95, type=c("basic", "norm",
"perc", "bca"))
Hope this helps,
Rui Barradas
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.4...@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" <annij...@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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