Re: [R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-18 Thread Joe Felsenstein

Emmanuel Paradis wrote:

> The new default for ace will be to use REML for continuous 
> characters and ML for discrete ones.

after Ted Garland wrote:

>>  Yes, we have always used REML for this!

(Emmanuel wrote: )

>>>   You can also try method="REML" which gives much better 
>>> estimates of sigma^2 than ML. I think I'll make it the 
>>> default for continuous characters.

** bragging mode on **

Glad to see you have all caught up to this paper:

Felsenstein, J. 1973. Maximum likelihood estimation
  of evolutionary trees from continuous characters.
  American Journal of Human Genetics 25: 471-492.

(which can be accessed at that journal free of charge)

** bragging mode off **

Joe

Joe Felsenstein, j...@gs.washington.edu
 Dept. of Genome Sciences, Univ. of Washington
 Box 355065, Seattle, WA 98195-5065 USA

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Re: [R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-18 Thread Emmanuel Paradis
Hi Ted,

The new default for ace will be to use REML for continuous characters and ML 
for discrete ones.

Cheers,

Emmanuel
-Original Message-
From: Theodore Garland Jr 
Date: Sat, 16 Mar 2013 16:22:59 
To: emmanuel.para...@ird.fr; Liam J. 
Revell; 
r-sig-phylo-boun...@r-project.org; Alejandro 
Gonzalez
Cc: R-phylo Mailing-list
Subject: RE: [R-sig-phylo] Ancestral state estimates of continuous traits

Yes, we have always used REML for this!

Cheers,
Ted

From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on 
behalf of Emmanuel Paradis [emmanuel.para...@ird.fr]
Sent: Friday, March 15, 2013 11:21 PM
To: Liam J. Revell; r-sig-phylo-boun...@r-project.org; Alejandro Gonzalez
Cc: R-phylo Mailing-list
Subject: Re: [R-sig-phylo] Ancestral state estimates of continuous traits

Alejandro and Liam,

You can also try method="REML" which gives much better estimates of sigma^2 
than ML. I think I'll make it the default for continuous characters.

Best,

Emmanuel
-Original Message-
From: "Liam J. Revell" 
Sender: r-sig-phylo-boun...@r-project.org
Date: Fri, 15 Mar 2013 14:23:20
To: Alejandro Gonzalez
Cc: R-phylo Mailing-list
Subject: Re: [R-sig-phylo] Ancestral state estimates of continuous traits

Hi Alejandro.

That must be a bug in ace(...,method="GLS").

I would also suggest you check out fastAnc in the phytools package. It
uses ace(...,method="pic") internally to take advantage of the fact that
the contrasts estimate at the root and the MLE assuming Brownian
evolution are the same. It re-roots the tree at all internal nodes which
sounds computationally intensive but is actually much faster than
getting the MLEs via numerical optimization.

fastAnc also uses equation (6) from Rohlf (2001) to get the correct 95%
interval on the estimates. My analysis
(http://blog.phytools.org/2013/02/new-version-of-fastanc-new-build-of.html)
suggests that the 95% CIs from ace(...,method="ML") are too small. (This
is probably because they rely on asymptotic properties of likelihood
that are not satisfied for the relatively small size of most
phylogenetic datasets.)

All the best, Liam

Liam J. Revell, Assistant Professor of Biology
University of Massachusetts Boston
web: http://faculty.umb.edu/liam.revell/
email: liam.rev...@umb.edu
blog: http://blog.phytools.org

On 3/15/2013 8:18 AM, Alejandro Gonzalez wrote:
> Hello,
>
> I am using ape to obtain ancestral state estimates for continuous
> traits. Two options are available, either maximum likelihood or a GLS
> method. I am comparing the results of both methods and one difference
> between the two puzzles me, I hope someone can enlighten me. Under GLS
> the ancestral state estimate at the root has virtually identical values
> for the point estimate and 95% confidence intervals, here is one
> example: 100 1.7848301 1.78483005 1.7848301 (100 is the root node
> number, then the ancestral state estimate and 95% CIs, respectively).
> However, when I use maximum likelihood for the same ancestral sate
> estimate, with the same data and tree I get the following result for the
> root :  100 1.6570119  0.86612615 2.4478977 (numbers in the same order
> as above).
> Any ideas as to why GLS gives such narrow confidence intervals for the
> ancestral state estimate at the basal node?
>
> Cheers
>
> Alejandro
> __
>
> Alejandro Gonzalez Voyer
>
> Post-doc
>
> Estaci�n Biol�gica de Do�ana
> Consejo Superior de Investigaciones Cient�ficas (CSIC)
> Av Am�rico Vespucio s/n
> 41092 Sevilla
> Spain
>
> Tel: + 34 - 954 466700, ext 1749
>
> E-mail: alejandro.gonza...@ebd.csic.es
>
> Web site (Under construction):
>
> Personal page: http://consevol.org/members/alejandro_combo.html
>
> Group page: http://consevol.org/people.html
>
> For PDF copies of papers see:
>
> http://csic.academia.edu/AlejandroGonzalezVoyer
>
>
>
>  [[alternative HTML version deleted]]
>
> ___
> 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-phylo@r-project.org/

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Re: [R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-16 Thread Theodore Garland Jr
Yes, we have always used REML for this!

Cheers,
Ted

From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on 
behalf of Emmanuel Paradis [emmanuel.para...@ird.fr]
Sent: Friday, March 15, 2013 11:21 PM
To: Liam J. Revell; r-sig-phylo-boun...@r-project.org; Alejandro Gonzalez
Cc: R-phylo Mailing-list
Subject: Re: [R-sig-phylo] Ancestral state estimates of continuous traits

Alejandro and Liam,

You can also try method="REML" which gives much better estimates of sigma^2 
than ML. I think I'll make it the default for continuous characters.

Best,

Emmanuel
-Original Message-
From: "Liam J. Revell" 
Sender: r-sig-phylo-boun...@r-project.org
Date: Fri, 15 Mar 2013 14:23:20
To: Alejandro Gonzalez
Cc: R-phylo Mailing-list
Subject: Re: [R-sig-phylo] Ancestral state estimates of continuous traits

Hi Alejandro.

That must be a bug in ace(...,method="GLS").

I would also suggest you check out fastAnc in the phytools package. It
uses ace(...,method="pic") internally to take advantage of the fact that
the contrasts estimate at the root and the MLE assuming Brownian
evolution are the same. It re-roots the tree at all internal nodes which
sounds computationally intensive but is actually much faster than
getting the MLEs via numerical optimization.

fastAnc also uses equation (6) from Rohlf (2001) to get the correct 95%
interval on the estimates. My analysis
(http://blog.phytools.org/2013/02/new-version-of-fastanc-new-build-of.html)
suggests that the 95% CIs from ace(...,method="ML") are too small. (This
is probably because they rely on asymptotic properties of likelihood
that are not satisfied for the relatively small size of most
phylogenetic datasets.)

All the best, Liam

Liam J. Revell, Assistant Professor of Biology
University of Massachusetts Boston
web: http://faculty.umb.edu/liam.revell/
email: liam.rev...@umb.edu
blog: http://blog.phytools.org

On 3/15/2013 8:18 AM, Alejandro Gonzalez wrote:
> Hello,
>
> I am using ape to obtain ancestral state estimates for continuous
> traits. Two options are available, either maximum likelihood or a GLS
> method. I am comparing the results of both methods and one difference
> between the two puzzles me, I hope someone can enlighten me. Under GLS
> the ancestral state estimate at the root has virtually identical values
> for the point estimate and 95% confidence intervals, here is one
> example: 100 1.7848301 1.78483005 1.7848301 (100 is the root node
> number, then the ancestral state estimate and 95% CIs, respectively).
> However, when I use maximum likelihood for the same ancestral sate
> estimate, with the same data and tree I get the following result for the
> root :  100 1.6570119  0.86612615 2.4478977 (numbers in the same order
> as above).
> Any ideas as to why GLS gives such narrow confidence intervals for the
> ancestral state estimate at the basal node?
>
> Cheers
>
> Alejandro
> __
>
> Alejandro Gonzalez Voyer
>
> Post-doc
>
> Estaci�n Biol�gica de Do�ana
> Consejo Superior de Investigaciones Cient�ficas (CSIC)
> Av Am�rico Vespucio s/n
> 41092 Sevilla
> Spain
>
> Tel: + 34 - 954 466700, ext 1749
>
> E-mail: alejandro.gonza...@ebd.csic.es
>
> Web site (Under construction):
>
> Personal page: http://consevol.org/members/alejandro_combo.html
>
> Group page: http://consevol.org/people.html
>
> For PDF copies of papers see:
>
> http://csic.academia.edu/AlejandroGonzalezVoyer
>
>
>
>  [[alternative HTML version deleted]]
>
> ___
> 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-phylo@r-project.org/

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Re: [R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-15 Thread Emmanuel Paradis
Alejandro and Liam,

You can also try method="REML" which gives much better estimates of sigma^2 
than ML. I think I'll make it the default for continuous characters.

Best,

Emmanuel
-Original Message-
From: "Liam J. Revell" 
Sender: r-sig-phylo-boun...@r-project.org
Date: Fri, 15 Mar 2013 14:23:20 
To: Alejandro Gonzalez
Cc: R-phylo Mailing-list
Subject: Re: [R-sig-phylo] Ancestral state estimates of continuous traits

Hi Alejandro.

That must be a bug in ace(...,method="GLS").

I would also suggest you check out fastAnc in the phytools package. It 
uses ace(...,method="pic") internally to take advantage of the fact that 
the contrasts estimate at the root and the MLE assuming Brownian 
evolution are the same. It re-roots the tree at all internal nodes which 
sounds computationally intensive but is actually much faster than 
getting the MLEs via numerical optimization.

fastAnc also uses equation (6) from Rohlf (2001) to get the correct 95% 
interval on the estimates. My analysis 
(http://blog.phytools.org/2013/02/new-version-of-fastanc-new-build-of.html) 
suggests that the 95% CIs from ace(...,method="ML") are too small. (This 
is probably because they rely on asymptotic properties of likelihood 
that are not satisfied for the relatively small size of most 
phylogenetic datasets.)

All the best, Liam

Liam J. Revell, Assistant Professor of Biology
University of Massachusetts Boston
web: http://faculty.umb.edu/liam.revell/
email: liam.rev...@umb.edu
blog: http://blog.phytools.org

On 3/15/2013 8:18 AM, Alejandro Gonzalez wrote:
> Hello,
>
> I am using ape to obtain ancestral state estimates for continuous
> traits. Two options are available, either maximum likelihood or a GLS
> method. I am comparing the results of both methods and one difference
> between the two puzzles me, I hope someone can enlighten me. Under GLS
> the ancestral state estimate at the root has virtually identical values
> for the point estimate and 95% confidence intervals, here is one
> example: 100 1.7848301 1.78483005 1.7848301 (100 is the root node
> number, then the ancestral state estimate and 95% CIs, respectively).
> However, when I use maximum likelihood for the same ancestral sate
> estimate, with the same data and tree I get the following result for the
> root :  100 1.6570119  0.86612615 2.4478977 (numbers in the same order
> as above).
> Any ideas as to why GLS gives such narrow confidence intervals for the
> ancestral state estimate at the basal node?
>
> Cheers
>
> Alejandro
> __
>
> Alejandro Gonzalez Voyer
>
> Post-doc
>
> Estaci�n Biol�gica de Do�ana
> Consejo Superior de Investigaciones Cient�ficas (CSIC)
> Av Am�rico Vespucio s/n
> 41092 Sevilla
> Spain
>
> Tel: + 34 - 954 466700, ext 1749
>
> E-mail: alejandro.gonza...@ebd.csic.es
>
> Web site (Under construction):
>
> Personal page: http://consevol.org/members/alejandro_combo.html
>
> Group page: http://consevol.org/people.html
>
> For PDF copies of papers see:
>
> http://csic.academia.edu/AlejandroGonzalezVoyer
>
>
>
>  [[alternative HTML version deleted]]
>
> ___
> 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-phylo@r-project.org/

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Re: [R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-15 Thread Liam J. Revell

Hi Alejandro.

That must be a bug in ace(...,method="GLS").

I would also suggest you check out fastAnc in the phytools package. It 
uses ace(...,method="pic") internally to take advantage of the fact that 
the contrasts estimate at the root and the MLE assuming Brownian 
evolution are the same. It re-roots the tree at all internal nodes which 
sounds computationally intensive but is actually much faster than 
getting the MLEs via numerical optimization.


fastAnc also uses equation (6) from Rohlf (2001) to get the correct 95% 
interval on the estimates. My analysis 
(http://blog.phytools.org/2013/02/new-version-of-fastanc-new-build-of.html) 
suggests that the 95% CIs from ace(...,method="ML") are too small. (This 
is probably because they rely on asymptotic properties of likelihood 
that are not satisfied for the relatively small size of most 
phylogenetic datasets.)


All the best, Liam

Liam J. Revell, Assistant Professor of Biology
University of Massachusetts Boston
web: http://faculty.umb.edu/liam.revell/
email: liam.rev...@umb.edu
blog: http://blog.phytools.org

On 3/15/2013 8:18 AM, Alejandro Gonzalez wrote:

Hello,

I am using ape to obtain ancestral state estimates for continuous
traits. Two options are available, either maximum likelihood or a GLS
method. I am comparing the results of both methods and one difference
between the two puzzles me, I hope someone can enlighten me. Under GLS
the ancestral state estimate at the root has virtually identical values
for the point estimate and 95% confidence intervals, here is one
example: 100 1.7848301 1.78483005 1.7848301 (100 is the root node
number, then the ancestral state estimate and 95% CIs, respectively).
However, when I use maximum likelihood for the same ancestral sate
estimate, with the same data and tree I get the following result for the
root :  100 1.6570119  0.86612615 2.4478977 (numbers in the same order
as above).
Any ideas as to why GLS gives such narrow confidence intervals for the
ancestral state estimate at the basal node?

Cheers

Alejandro
__

Alejandro Gonzalez Voyer

Post-doc

Estaci�n Biol�gica de Do�ana
Consejo Superior de Investigaciones Cient�ficas (CSIC)
Av Am�rico Vespucio s/n
41092 Sevilla
Spain

Tel: + 34 - 954 466700, ext 1749

E-mail: alejandro.gonza...@ebd.csic.es

Web site (Under construction):

Personal page: http://consevol.org/members/alejandro_combo.html

Group page: http://consevol.org/people.html

For PDF copies of papers see:

http://csic.academia.edu/AlejandroGonzalezVoyer



 [[alternative HTML version deleted]]

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[R-sig-phylo] Ancestral state estimates of continuous traits

2013-03-15 Thread Alejandro Gonzalez
Hello,

I am using ape to obtain ancestral state estimates for continuous traits. Two 
options are available, either maximum likelihood or a GLS method. I am 
comparing the results of both methods and one difference between the two 
puzzles me, I hope someone can enlighten me. Under GLS the ancestral state 
estimate at the root has virtually identical values for the point estimate and 
95% confidence intervals, here is one example: 100 1.7848301 1.78483005 
1.7848301 (100 is the root node number, then the ancestral state estimate and 
95% CIs, respectively). However, when I use maximum likelihood for the same 
ancestral sate estimate, with the same data and tree I get the following result 
for the root :  100 1.6570119  0.86612615 2.4478977 (numbers in the same order 
as above).
Any ideas as to why GLS gives such narrow confidence intervals for the 
ancestral state estimate at the basal node?

Cheers

Alejandro
__

Alejandro Gonzalez Voyer

Post-doc

Estación Biológica de Doñana
Consejo Superior de Investigaciones Científicas (CSIC)
Av Américo Vespucio s/n
41092 Sevilla
Spain

Tel: + 34 - 954 466700, ext 1749

E-mail: alejandro.gonza...@ebd.csic.es

Web site (Under construction):

Personal page: http://consevol.org/members/alejandro_combo.html

Group page: http://consevol.org/people.html

For PDF copies of papers see:

http://csic.academia.edu/AlejandroGonzalezVoyer



[[alternative HTML version deleted]]

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