Hi Franz,
Look at this paper :
http://onlinelibrary.wiley.com/doi/10./j.1365-2745.2010.01717.x/abstract
Em 28/07/2017 07:03, escreveu:
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Today's Topics:
1. phylogenetic circular linear regression (f.k...@mailbox.org)
2. Re: phylogenetic circular linear regression (Florian Boucher)
3. Re: phylogenetic circular linear regression (Florian Boucher)
4. Re: selecting a set of incongruent trees from a posterior
distribution (Jesse Delia)
5. Re: phylogenetic circular linear regression (Peter Smits)
--
Message: 1
Date: Thu, 27 Jul 2017 13:06:49 +0200
From: "f.k...@mailbox.org"
To: r-sig-phylo
Subject: [R-sig-phylo] phylogenetic circular linear regression
Message-ID:
Content-Type: text/plain; charset=utf-8
Hi all,
it there something like a phylogenetic circular linear regression or such?
I want to test if the hue (circular 360?) of species differs between two
lifestyles?
Hope someone can help?
If this is not there please also let me know.
Cheers,
Franz
--
Message: 2
Date: Thu, 27 Jul 2017 14:09:27 +0200
From: Florian Boucher
To: "f.k...@mailbox.org"
Cc: r-sig-phylo
Subject: Re: [R-sig-phylo] phylogenetic circular linear regression
Message-ID:
Content-Type: text/plain; charset="UTF-8"
Hi Franz,
I don't know about anything like what you propose but maybe you could
sine-transform your trait and then use phylogenetic linear or logistic
regression?
Florian
2017-07-27 13:06 GMT+02:00 f.k...@mailbox.org :
> Hi all,
>
> it there something like a phylogenetic circular linear regression or such?
>
> I want to test if the hue (circular 360?) of species differs between two
> lifestyles?
>
> Hope someone can help?
>
> If this is not there please also let me know.
>
> Cheers,
> Franz
>
> ___
> R-sig-phylo mailing list - R-sig-phylo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
> Searchable archive at http://www.mail-archive.com/r-
> sig-ph...@r-project.org/
[[alternative HTML version deleted]]
--
Message: 3
Date: Thu, 27 Jul 2017 16:55:06 +0200
From: Florian Boucher
To: "f.k...@mailbox.org"
Cc: r-sig-phylo
Subject: Re: [R-sig-phylo] phylogenetic circular linear regression
Message-ID:
Content-Type: text/plain; charset="UTF-8"
Hi again Frank,
I just realized that a sine or cosine transformation would leave you with
opposite colors on the hue having the same value... probably not so handy.
Sorry, that was a poor suggestion...
Florian
2017-07-27 14:09 GMT+02:00 Florian Boucher :
> Hi Franz,
>
> I don't know about anything like what you propose but maybe you could
> sine-transform your trait and then use phylogenetic linear or logistic
> regression?
>
> Florian
>
> 2017-07-27 13:06 GMT+02:00 f.k...@mailbox.org :
>
>> Hi all,
>>
>> it there something like a phylogenetic circular linear regression or
such?
>>
>> I want to test if the hue (circular 360?) of species differs between two
>> lifestyles?
>>
>> Hope someone can help?
>>
>> If this is not there please also let me know.
>>
>> Cheers,
>> Franz
>>
>> ___
>> R-sig-phylo mailing list - R-sig-phylo@r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
>> Searchable archive at http://www.mail-archive.com/r-
>> sig-ph...@r-project.org/
>
>
>
[[alternative HTML version deleted]]
--
Message: 4
Date: Thu, 27 Jul 2017 15:11:54 -0400
From: Jesse Delia
To: Jarrod Hadfield
Cc: Santiago S?nchez ,
r-sig-phylo@r-project.org, "ear...@gmail.com"
Subject: Re: [R-sig-phylo] selecting a set of incongruent trees from a
posterior distribution
Message-ID:
Content-Type: text/plain; charset="UTF-8"
Thank you everyone for your help, I really appreciate it!
On Wed, Jul 26, 2017 at 11:55 AM, Jarrod Hadfield
wrote:
> Hi Jesse,
>
> In order to account for phylogenetic uncertainty you are better just
> pulling trees from their posterior rather than choosing trees that are
> incongruent. The latter will give estimates biased toward those associated
> with extreme trees.
>
> If the analysis is the binomial model you posted on R-sig-mixed you can
> speed up the analysis by passing the latent variables from one model as
the
> starting values in the next model without a long burn-in. If the data are
> Gaussian you just nee
