I'd be grateful for defences of "bootstrap confidence intervals"
(and discussion of other intervals generated by bootstrapping)
-- not least because I'll be teaching bootstrapping next year!
Please e-mail me, and I'll summarise to the net.
-- Ewart Shaw
===================ORIGINAL COMMENTS FOLLOW=========================
The idea of using the bootstrap to obtain CI's has always
struck me as perverse, since one is simultaneously assuming:
(A) (for bootstrapping) The underlying population distribution is
precisely the same as the observed sample distribution.
(B) (to get a CI) The underlying population distribution is not
necessarily the same as the observed sample distribution.
If you add to (A) "...except for a location shift",
then there is no non-zero shift that would make any other
population distribution compatible with the observed data
(unless, for example, you have observed some data at all integer
values, and are only considering possible integer location shifts!)
I suspect this is at bottom a criticism of CI's, not of the bootstrap.
======================================================================
--
J.E.H.Shaw, Department of Statistics, | JANET: strgh@uk.ac.warwick
University of Warwick, | BITNET: strgh%uk.ac.warwick@UKACRL
Coventry CV4 7AL, U.K. | PHONE: +44 203 523069
An ex-algebraist who lost his ideals, his associates, and finally his identity