PEM-class: Class and Methods for Phylogenetic Eigenvector Maps (PEM)
In MPSEM: Modeling Phylogenetic Signals using Eigenvector Maps

Description Usage Arguments Format Details Functions Author(s) References See Also

Class and methods to handle Phylogenetic Eigenvector Maps (PEM).

## S3 method for class 'PEM'
print(x, ...)

## S3 method for class 'PEM'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

## S3 method for class 'PEM'
predict(
  object,
  targets,
  lmobject,
  newdata,
  interval = c("none", "confidence", "prediction"),
  level = 0.95,
  ...
)

`x`	A `PEM-class` object containing a Phylogenetic Eigenvector Map.
`...`	Additional parameters to be passed to the method. Currently ignored.
`row.names`	Included for method consistency reason; ignored.
`optional`	Included for method consistency reason; ignored.
`object`	A `PEM-class` object.
`targets`	Output of `getGraphLocations`.
`lmobject`	An object of class ‘lm’ (see `lm` for details).
`newdata`	Auxiliary trait values.
`interval`	The kind of limits (confidence or prediction) to return with the predictions; `interval="none"`: do not return a confidence interval.
`level`	Probability of the confidence of prediction interval.

A PEM-class object contains:

x: The graph-class object that was used to build the PEM (see PEM.build).
sp: A logical vector specifying which vertex is a tip.
B: The influence matrix for those vertices that are tips.
ne: The number of edges.
nsp: The number of species (tips).
Bc: The column-centred influence matrix.
means: The column means of B.
dist: Edge lengths.
a: The steepness parameter (see PEM.build for details).
psi: The relative evolution rate along the edges (see PEM.build for details).
w: Edge weights.
BcW: The weighted and column-centred influence matrix.
d: The singular values of BcW.
u: The eigenvectors (left singular vectors) of BcW.
vt: The right singular vectors of BcW.

In addition to these standard component, function, PEM.fitSimple and PEM.forcedSimple add the following members, which are necessary to make predictions:

S2: The variances of responses (one value for each response).
y: A copy of the responses.
opt: The list returned by optim.

The estimated weighting parameters are also given as an edge property.

The print method provides the number of eigenvectors, the number of observations these vectors are spanning, and their associated eigenvalues.

The as.data.frame method extracts the eigenvectors from the object and allows one to use PEM-class objects as data parameter in function such as lm and glm.

The predict object is a barebone interface meant to make predictions. It must be given species locations with respect to the phylogenetic graph (target), which are provided by function getGraphLocations and a linear model in the form of an object from lm. The user must provide auxiliary trait values if lmobject involves such trait.

print.PEM: Print method for PEM-class objects
as.data.frame.PEM: Method as.data.frame for PEM-class objects
predict.PEM: Predict method for PEM-class objects

Guillaume Guenard, with contribution from Pierre Legendre Maintainer: Guillaume Guenard <guillaume.guenard@gmail.com>

Guénard, G., Legendre, P., and Peres-Neto, P. 2013. Phylogenetic eigenvector maps (PEM): a framework to model and predict species traits. Meth. Ecol. Evol. 4: 1120–1131

PEM.build, PEM-class

MPSEM documentation built on Jan. 14, 2022, 1:07 a.m.