Ah -- I get it now. Even my rescaled trait data have the
same width 95% CI, e.g. my CI for a particular node could be
mean +/- 2.345 whether my input trait data ranges from
0.3-0.5, or 400-800.
My "fix" with scaled data occurred because I was
back-transforming, which scaled the size of the 95% CI with
the size of the mean. So I guess neither of these options
is a "real" estimate of the CI, unlike when one runs ace,
method=ML.
I noticed the same behavior using ace, method="gls", so that
should be noted as well. I have been using method="ml" for
ancestral character estimation, the width of its CIs vary as
you might expect, so I was just surprised when PIC & GLS
didn't exhibit the same behavior.
Cheers,
Nick
On 3/24/11 12:21 AM, Nick Matzke wrote:
On Wed, Mar 23, 2011 at 10:24 PM, Emmanuel Paradis
<emmanuel.para...@ird.fr> wrote:
Hi Nick,
With method = "pic", the CIs are computed using the expected variances under
the model, so they depend only on the tree. I've added a paragraph in the
man page to explain this.
Cheers,
Emmanuel
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