You mentioned the boot package, I've just stumbled across a package
called simpleboot, with a function lm.boot. Would this be suitable - it
says I can sample cases from the origional dataset, as well as from the
residuals of a model. Not all the options I understand but I assume the
defaults might be suitable for what I'm doing?
On 04/01/2011 17:56, Ben Ward wrote:
Ok I'll check I understand:
So it's using sample, to resample d once, 10 values, because the rnorm
has 10 values, with replacement (I assume thats the TRUE part).
Then a for loop has this to resample the data - in the loop's case its
1000 times. Then it does a lm to get the coefficients and add them to
d1.coef. I'm guessing that the allboot bit with rbind, which is null
at the start of the loop, is the collection of d1.coef values, as I
think that without it, every cycle of the loop the d1.coef from the
previous cycle round the loop would be gone?
On 04/01/2011 16:24, Dieter Menne wrote:
Axolotl9250 wrote:
...
resampled_ecoli = sample(ecoli, 500, replace=T)
coefs = (coef(lm(MIC. ~ 1 + Challenge + Cleaner + Replicate,
data=resampled_ecoli)))
sd(coefs)
...
Below a simplified and self-consistent version of your code, and some
changes
Dieter
# resample
d = data.frame(x=rnorm(10))
d$y = d$x*3+rnorm(10,0.01)
# if you do this, you only get ONE bootstrap sample
d1 = d[sample(1:nrow(d),10,TRUE),]
d1.coef = coef(lm(y~x,data=d1))
d1.coef
# No error below, because you compute the sd of (Intercept) and slope
# but result is wrong!
sd(d1.coef)
# We have to do this over and over
# Check ?replicate for a more R-ish approach....
nsamples = 1000
allboot = NULL
for (i in 1:1000) {
d1 = d[sample(1:nrow(d),10,TRUE),]
d1.coef = coef(lm(y~x,data=d1))
allboot = rbind(allboot,d1.coef) # Not very efficient, preallocate!
}
head(allboot) # display first of nsamples lines
apply(allboot,2,mean) # Compute mean
apply(allboot,2,sd) # compute sd
# After you are sure you understood the above, you might try package
boot.
______________________________________________
R-help@r-project.org mailing list
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@r-project.org mailing list
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.
