[R-sig-phylo] PGLS vs OUwie?
Hi all, This may be a very basic question, but I have been racking my brain since my advisor asked me yesterday in our meeting. What are the fundamental differences (if any) between GLS (PGLS) and something like ouch or OUwie? If there is already literature related to this, please feel free to just point me in that direction. Thanks in advance, Will -- William Gearty PhD Student, Paleobiology Department of Geological Sciences Stanford School of Earth, Energy Environmental Sciences people.stanford.edu/wgearty [[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/
Re: [R-sig-phylo] Off-diagonal elements in multivariate OU evolution
Hi Cody, Yes you can use this approach to test whether there is a significant interaction between traits toward the optimum. Alternatively you can sum the log-likelihood of two separate univariate analysis for the independent analysis.The estimated variance-covariance matrix is probably near singularity, have you try different methods for computing the likelihood? (although it may take some times for a 6000 tips tree...) Best, Julien Date: Tue, 5 May 2015 17:17:59 -0400 From: codyj...@gmail.com To: r-sig-phylo@r-project.org Subject: [R-sig-phylo] Off-diagonal elements in multivariate OU evolution Hi all, I have a large dataset (~6000 species) including two traits of interest. I am hoping to test whether the extant patterns are more consistent with each trait evolving independently under OU processes (with 1 regime per trait) or if the traits have co-evolved in some manner (i.e. the traits influence one another's optima). I have been trying to use mvMORPH and mvSLOUCH to fit two models (one of independent evolution, and one of dependent evolution) using the code below. My plan was then to compare AIC values from the two models. From what I gather, the off-diagonal elements of the alpha and sigma matrix determine whether there is co-evolution of the trait optima, and the stochastic element of the OU processes, respectively. ##in mvMORPH independ.evolv-mvOU(tree, data, model=OU1, param=list(alpha=constraint, sigma=constraint)) depend.evolv-mvOU(tree, data, model=OU1, param=list(alpha=NULL, sigma=NULL)) ##and a similar thing in mvSLOUCH independ.evolv-ouchModel(tree, data, regimes=NULL, Atype=Diagonal, Syytype=Diagonal) depend.evolv-ouchModel(tree, data, regimes=NULL, Atype=DecomposableReal, Syytype=UpperTri) My questions are: 1. Is my interpretation of these models correct? Specifically I am concerned about the interpretation of the alpha matrix. I am somewhat confused as to how the off-diagonal alpha elements influence the OU process when I have specified 1 regime per trait. 2. I am frequently encountering errors during model fitting in mvMORPH of the typeError in loglik_mvmorph(dat, matEstim$V, matEstim$W, n, p, error = error, : the leading minor of order 5833 is not positive definite. I gather this has to do with a problem in the matrix decomposition, but is there a practical solution? I have tried some of the other 'decomp' options but this does not seem to help. 3. I had a few emails with Krzysztof Bartoszek (author of mvSLOUCH) and he suggested that such a large dataset would be problematic. Would this be an issue for mvMORPH as well? If so, is there a generally acceptable work-around for reducing the size of comparative data sets to accommodate models like this? Many thanks in advance Cody Dey codyj...@gmail.com McMaster University Department of Biology [[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/ [[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/
Re: [R-sig-phylo] PGLS vs OUwie?
Dear Will, I suggest that you read the Appendix in this paper Lavin et al. (2008) (available on my website) and then the original papers by Butler and King on OUCH, etc. http://www.jstor.org/stable/10.1086/590395 Cheers, Ted Theodore Garland, Jr., Professor Department of Biology University of California, Riverside Riverside, CA 92521 Office Phone: (951) 827-3524 Facsimile: (951) 827-4286 (not confidential) Email: tgarl...@ucr.edu http://www.biology.ucr.edu/people/faculty/Garland.html http://scholar.google.com/citations?hl=enuser=iSSbrhwJ Director, UCR Institute for the Development of Educational Applications Editor in Chief, Physiological and Biochemical Zoology Fail Lab: Episode One http://testtube.com/faillab/zoochosis-episode-one-evolution http://www.youtube.com/watch?v=c0msBWyTzU0 From: R-sig-phylo [r-sig-phylo-boun...@r-project.org] on behalf of William Gearty [wgea...@stanford.edu] Sent: Tuesday, May 05, 2015 8:39 AM To: r-sig-phylo Subject: [R-sig-phylo] PGLS vs OUwie? Hi all, This may be a very basic question, but I have been racking my brain since my advisor asked me yesterday in our meeting. What are the fundamental differences (if any) between GLS (PGLS) and something like ouch or OUwie? If there is already literature related to this, please feel free to just point me in that direction. Thanks in advance, Will -- William Gearty PhD Student, Paleobiology Department of Geological Sciences Stanford School of Earth, Energy Environmental Sciences people.stanford.edu/wgearty [[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/
Re: [R-sig-phylo] PGLS vs OUwie?
Hi William, �ouch� and �OUwie� are based on Generalized Least Squares (GLS). Indeed, �generalized� mean that we can fit a linear model with between species hierarchical structure ( given e.g. by interspecies evolutionary variances-covariances according to an Ornstein-Uhlenbeck process) Nevertheless, it�s true that in most papers you will often find the term (P)GLS when a linear model with one response variable and one predictor variable is fitted. Methods such as �ouch� and �OUwie� fit a model without intercept (or predictor variable) but there is no differences in the statistical machinery behind� Best, Julien From: wgea...@stanford.edu Date: Tue, 5 May 2015 08:39:17 -0700 To: R-sig-phylo@r-project.org Subject: [R-sig-phylo] PGLS vs OUwie? Hi all, This may be a very basic question, but I have been racking my brain since my advisor asked me yesterday in our meeting. What are the fundamental differences (if any) between GLS (PGLS) and something like ouch or OUwie? If there is already literature related to this, please feel free to just point me in that direction. Thanks in advance, Will -- William Gearty PhD Student, Paleobiology Department of Geological Sciences Stanford School of Earth, Energy Environmental Sciences people.stanford.edu/wgearty [[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/ [[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] Off-diagonal elements in multivariate OU evolution
Hi all, I have a large dataset (~6000 species) including two traits of interest. I am hoping to test whether the extant patterns are more consistent with each trait evolving independently under OU processes (with 1 regime per trait) or if the traits have co-evolved in some manner (i.e. the traits influence one another's optima). I have been trying to use mvMORPH and mvSLOUCH to fit two models (one of independent evolution, and one of dependent evolution) using the code below. My plan was then to compare AIC values from the two models. From what I gather, the off-diagonal elements of the alpha and sigma matrix determine whether there is co-evolution of the trait optima, and the stochastic element of the OU processes, respectively. ##in mvMORPH independ.evolv-mvOU(tree, data, model=OU1, param=list(alpha=constraint, sigma=constraint)) depend.evolv-mvOU(tree, data, model=OU1, param=list(alpha=NULL, sigma=NULL)) ##and a similar thing in mvSLOUCH independ.evolv-ouchModel(tree, data, regimes=NULL, Atype=Diagonal, Syytype=Diagonal) depend.evolv-ouchModel(tree, data, regimes=NULL, Atype=DecomposableReal, Syytype=UpperTri) My questions are: 1. Is my interpretation of these models correct? Specifically I am concerned about the interpretation of the alpha matrix. I am somewhat confused as to how the off-diagonal alpha elements influence the OU process when I have specified 1 regime per trait. 2. I am frequently encountering errors during model fitting in mvMORPH of the typeError in loglik_mvmorph(dat, matEstim$V, matEstim$W, n, p, error = error, : the leading minor of order 5833 is not positive definite. I gather this has to do with a problem in the matrix decomposition, but is there a practical solution? I have tried some of the other 'decomp' options but this does not seem to help. 3. I had a few emails with Krzysztof Bartoszek (author of mvSLOUCH) and he suggested that such a large dataset would be problematic. Would this be an issue for mvMORPH as well? If so, is there a generally acceptable work-around for reducing the size of comparative data sets to accommodate models like this? Many thanks in advance Cody Dey codyj...@gmail.com McMaster University Department of Biology [[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/
