Tools for studying the evolution of high-dimensional traits (in particular, function-valued traits), including ancestral state reconstruction, estimating phylogenetic signal, and assessing correlated trait evolution.

Package: | phylocurve |

Type: | Package |

Version: | 2.0.7 |

Date: | 2016-12-01 |

License: | GPL (>= 2) |

Eric W. Goolsby <eric.goolsby.evolution@gmail.com>

Goolsby, E.W. 2015. "Phylogenetic comparative methods for evaluating the evolutionary history of function-valued traits." Systematic Biology. In press.

Adams, D.C. 2014. A method for assessing phylogenetic least squares models for shape and other high-dimensional multivariate data. Evolution. 68:2675-2688.

Adams, D.C. 2014. A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data. Systematic Biology. 63:685-697.

Ho, L. S. T. and Ane, C. 2014. "A linear-time algorithm for Gaussian and non-Gaussian trait evolution models". Systematic Biology 63(3):397-408.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
require(phytools)
# simulate evolution of a function-valued trait (glm with logit link)
sim_data <- sim.curves()
# perform ancestral curve reconstruction
anc_recon <- phylocurve(y~x,tree = sim_data$tree,data = sim_data$data)
# get tip coefficients and aligned function data
tip_coefficients <- get.tip.coefficients(formula = y~x,tree = sim_data$tree,data = sim_data$data)
data <- get.aligned.function.data(tip_coefficients)
# estimate evolutionary rates
evo.model.fitted <- evo.model(sim_data$tree,data)
``` |

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