Re: About the Bootstrap...

> iii. A parametric bootstrap generates its pseudoreplicate data sets
> using an explicit model of evolution abstracted from the data, rather
> than resampling the actual data as in a non-parametric bootstrap. If,
> for example, I wanted to get bootstrapped data sets for a set of DNA
> sequences, I might first estimate a tree using some phylogenetic
> analysis program, then estimate evolutionary parameters over that tree
> (transition/transversion ratio, proportion of invariable sites, base
> composition, etc.), and then plug those parameters and that tree into an
> evolution simulation program to get a new data set. Repeated many times,
> I would have a set of pseudoreplicate data sets. Those pseudoreplicates
> can then be used for all sorts of purposes. See this for example:
>
> Huelsenbeck, J. P., D. M. Hillis, and R. Jones. 1996. Parametric
> bootstrapping in molecular phylogenetics: Applications and performance.
> Pages 19-45 in  Molecular zoology: Advances, strategies, and protocols
> (J. D. Ferraris and S. R. Palumbi, eds.). Wiley.

Many thanks for this. The procedure you describe is what I put in the
solution # i -- sorry: I didn't explain it very well.

That's OK for me, but consequently, how to name -- if a specific name
exists... -- the parametric (as based on parametric estimates of descriptors
uncertainties) Monte-Carlo resampling procedure described in (ii)? Actually,
in the case of biometrical and/or morphometrical data, the procedure you
describe seems to me hard to apply, even if an explicit model of biometrical
and/or morphometrical evolution can be formulated from the data (e.g., taking
into account the variances and covariances between descriptors by using the
Mahalanobis generalized distance). The procedure proposed in (ii) is much
more easy and straightforward, but I currently don't know any paper dealing
with it on a theoretical basis. For instance, when I apply this procedure on
real data sets (I have done the programs for this), and I compare estimated
CL with CL estimates obtained by classical nonparametric bootstrap, it (the
ii procedure) appears to return significantly higher CL estimates, and thus
to be significantly less conservative than the nonparametric bootstrap
technique. But how to interpret such differences?

Gilles.