Resampling to find Confidence intervals

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.