On Sat, 13 Jan 2024 17:59:16 -0500
Duncan Murdoch <murdoch.dun...@gmail.com> wrote:
<SNIP>
> My guess is that one of the bootstrap samples had a different
> selection of countries, so factor(Country) had different levels, and
> that would really mess things up.
>
> You'll need to decide how to handle that: If you are trying to
> estimate the coefficient for Italy in a sample that contains no data
> from Italy, what should the coefficient be?
Perhaps NA? Ben Bolker conjectured that boot() might be able to handle
this. Getting the NAs into the coefficients is a bit of a fag, but. I
tried:
func <- function(data, idx) {
clyde <- coef(lm(Score~ Time + factor(Country),data=data))
ccc <- coef(lm(Score~ Time + factor(Country),data=data[idx,]))
urk <- rep(NA,length(clyde))
names(urk) <-names(clyde)
urk[names(ccc)] <- ccc
urk
}
It produced a result:
> > set.seed(42)
> > B= boot(e, func, R=1000)
> B
>
> ORDINARY NONPARAMETRIC BOOTSTRAP
>
>
> Call:
> boot(data = e, statistic = func, R = 1000)
>
>
> Bootstrap Statistics :
> original bias std. error
> t1* 609.62500 3.6204052 95.39452
> t2* -54.81250 -1.6624704 36.32911
> t3* -41.33333 -2.7337992 100.72113
> t4* -96.00000 -1.0995718 99.78864
> t5* -126.00000 -0.6548886 63.47076
> t6* -26.33333 -1.6516683 87.80483
> t7* -15.66667 -0.8391170 91.72467
> t8* -21.66667 -5.4544013 83.69211
> t9* 18.33333 -0.7711001 85.57278
However I have no idea if the result is correct, or even meaningful. I
have no idea what I'm doing. Just hammering and hoping. 😊️
<SNIP>
cheers,
Rolf
--
Honorary Research Fellow
Department of Statistics
University of Auckland
Stats. Dep't. (secretaries) phone:
+64-9-373-7599 ext. 89622
Home phone: +64-9-480-4619
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