tools:::Rd_package_description("MPSEM")
tools:::Rd_package_author("MPSEM") Maintainer: tools:::Rd_package_maintainer("MPSEM")
Phylogenetic eignevector maps (PEM) is a method for using phylogeny to model features of organism, most notably quantitative traits. It consists in calculating sets of explanatory variables (eigenvectors) that are meant to represent different patterns in trait values that are likely to have been inducted by evolution. These patterns are used to model the data, using a linear model for instance.
If one in interested in a ‘target’ species (i.e. a species for which the trait value is unknown), and provided that we know the phylogenetic relationships between that species and those of the model, the method allows us to obtain the scores of that new species on the phylogenetic eigenfunctions underlying a PEM. These scores are used to make empirical predictions of trait values for the target species on the basis of those observed for the species used in the model.
Functions PEM.build, PEM.updater,
PEM.fitSimple, and PEM.forcedSimple allow one to
build, update (i.e. recalculate with alternative weighting parameters) as well
as to estimate or force arbitrary values for the weighting function
parameters.
Functions getGraphLocations and
Locations2PEMscores allow one to make predictions using method
predict.PEM and a linear model. To obtain this linear model,
one can use either function lm or auxiliary functions
lmforwardsequentialsidak or
lmforwardsequentialAICc, which perform forward-stepwise
variable addition on the basis of either familiwise type I error rate or the
Akaike Information Criterion (AIC), respectively.
The package provides low-level utility functions for performing operations on
graphs (see graph-functions), calculate influence matrix
(PEMInfluence), and simulate trait values (see
trait-simulator).
A phylogenetic modelling tutorial using MPSEM is available as a
package vignette. See example below.
The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("MPSEM") tools:::Rd_package_indices("MPSEM")
Guénard, G., Legendre, P., and Peres-Neto, P. 2013. Phylogenetic eigenvector maps: a framework to model and predict species traits. Methods in Ecology and Evolution 4: 1120-1131
Makarenkov, V., Legendre, P. & Desdevise, Y. 2004. Modelling phylogenetic relationships using reticulated networks. Zoologica Scripta 33: 89-96
Blanchet, F. G., Legendre, P. & Borcard, D. 2008. Modelling directional spatial processes in ecological data. Ecological Modelling 215: 325-336
## To view MPSEM tutorial
vignette("MPSEM", package="MPSEM")
Run the code above in your browser using DataLab