MPSEM (version 0.3-6)

MPSEM-package: MPSEM

Description

MPSEM

Details

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 patters 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 gets a ‘target’ species (i.e. a species for which the trait value is unknown), and providing that we know the phylogenetic relationships between that species and those of the model, the method allows 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 of the model.

Functions PEM.build, PEM.updater, PEM.fitSimple, and PEM.forcedSimple allows one to build, update (i.e. recalculate with alternate weighting parameters) as well as to estimate or force arbitrary values for the weighting function parameters.

Functions getGraphLocations and Locations2PEMscores allows one to make predictions using method predict.PEM and a linear model. To obtain these linear model, user can use 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 function for performing operation on graphs (see graph-functions), calculate influence matrix (PEMInfluence), and simulate trait values (see trait-simulator).

A phylogenetic modeling tutorial using MPSEM is available as a vignette (see example below).

The DESCRIPTION file: MPSEM MPSEM

References

Gu<U+00E9>nard, G., Legendre, P., and Peres-Neto, P. 2013. Phylogenetic eigenvector maps (PEM): a framework to model and predict species traits. Meth. Ecol. Evol. In press.

See Also

Makarenkov, V., Legendre, L. & Desdevise, Y. 2004. Modelling phylogenetic relationships using reticulated networks. Zool. Scr. 33: 89-96

Blanchet, F. G., Legendre, P. & Borcard, D. 2008. Modelling directional spatial processes in ecological data. Ecol. Model. 215: 325-336

Examples

# NOT RUN {
  ### To view MPSEM tutorial
  vignette("MPSEM", package="MPSEM")
# }