Dear Marguerite and everyone,
thank you very much for your considerate postings. I have reconsidered my
analyses and excluded the zero values, because they indicate absence of the
trait rather than are part of the continuum of values. Instead, I analyzed the
data as a 1) discrete trait:
Dear fellow list users,
I would like to assess the magnitude of phylogenetic signal in two sets of
continuous data. Set 1 contains numerous zeros and is therefore non-normal. Set
2 contains very little variation and is non-normal due to underdispersion.
Given that both data sets are largely
Hello,
The library picante in R implements Blomberg et al (2003) K estimate, Liam's
phytools package does as well. Phytools has the added advantage, if I remember
correctly, of allowing users to estimate K including within species variation.
Cheers
Alejandro
On 25, Apr 2012, at 5:29 PM,
However, calculating a K statistic is strange when the data are not thought of
as continuous-valued and/or evolving similar to Brownian motion. The
randomization test is OK, however.
Cheers,
Ted
From: Alejandro Gonzalez [alejandro.gonza...@ebd.csic.es]
Sent: Wednesday, April 25, 2012 8:46 AM
Thanks all for your helpful contributions! I will use phylosignal.
Ted, I'm not sure I understand your last comment, when the data are not though
of as continuous-valued and/or evolving similar to Brownian motion. What do
you mean by that? Also, are you suggesting that I report the
Read over the Blomberg et al. (2003) paper.
K is intended for continuous-valued traits and/or those evolving similar to
Brownian motion.
You could report it if you wished, but I would add that caveat if you do.
The randomization test should be robust in any case.
Cheers,
Ted
From: Nina
Hi Nina and everyone,
One thing to consider is that not all zero data are the same. Zeros under a
model of continuous trait evolution with a gaussian process as assumed under
Brownian motion and OU processes would occasionally cross zero, maybe go
negative, etc. For example if you were
