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 liam.rev...@umb.edu Sender: r-sig-phylo-boun...@r-project.org Date: Fri, 15 Mar 2013 14:23:20 To: Alejandro Gonzalezalejandro.gonza...@ebd.csic.es Cc: R-phylo Mailing-listr-sig-phylo@r-project.org 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/ ___ 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/ ___ 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/
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 liam.rev...@umb.edu Sender: r-sig-phylo-boun...@r-project.org Date: Fri, 15 Mar 2013 14:23:20 To: Alejandro Gonzalezalejandro.gonza...@ebd.csic.es Cc: R-phylo Mailing-listr-sig-phylo@r-project.org 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/ ___ 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/ ___ 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/ ___ 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/
[R-sig-phylo] Ancestral state estimates of continuous traits
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]] ___ 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/
