fast.SSC: Fast Phylogenetic Signal Using Sum of Squared Changes (SSC)

In Rphylopars: Phylogenetic Comparative Tools for Missing Data and Within-Species Variation

Fast Phylogenetic Signal Using Sum of Squared Changes (SSC)

Description

This function uses a fast ancestral state reconstruction algorithm (anc.recon, Goolsby, In review) to calculate the sum of squared changes bewteen ancestral and descendant nodes/tips, as described in Klingenberg and Gidaszewski (2010). Significance is assessed via phylogenetic permutation.

Usage

fast.SSC(trait_data, tree, niter = 1000)

Arguments

trait_data	A vector or matrix of trait values. Names or row names correspond to species names. Data cannot have any missing data or within-species variation.
tree	An object of class phylo.
niter	Number of iterations for hypothesis testing (default=1000).

Value

pvalue	Description of 'comp1'
scaled.SSC	Scaled sum of squared changes. A value less than 1 indicates less phylogenetic signal as measured by SSC than expected under Brownian motion, and a value greater than 1 indicates greater phylogenetic signal as measured by SSC than expected under Brownian motion.
SSC	Total sum of squared changes (SSC)

Author(s)

Eric W. Goolsby

References

Goolsby E.W. 2016. Likelihood-Based Parameter Estimation for High-Dimensional Phylogenetic Comparative Models: Overcoming the Limitations of 'Distance-Based' Methods. Systematic Biology. Accepted.

Blomberg SP, Garland T, Ives AR. 2003. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution, 57:717-745.

Klingenberg, C. P., and N. A. Gidaszewski. 2010. Testing and quantifying phylogenetic signals and homoplasy in morphometric data. Syst. Biol. 59:245-261.

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.

Examples

sim_dat <- simtraits(ntaxa = 100,ntraits = 4)
fast.SSC(trait_data = sim_dat$trait_data,tree = sim_dat$tree)

Rphylopars documentation built on May 9, 2022, 9:08 a.m.