phylolm (version 2.0)

phyloglm: Phylogenetic Generalized Linear Model

Description

Fits a phylogenetic generalized linear model. The computation uses an algorithm that is linear in the number of tips in the tree.

Usage

phyloglm(formula, data = list(), phy, model = c("LogReg"), 
                  btol = 10, log.alpha.bound = 4)

Arguments

formula

a model formula.

data

a data frame containing variables in the model. If not found in data, the variables are taken from the current environment.

phy

a phylogenetic tree of type phylo with branch lengths.

model

Currently, only phylogenetic logistic regression is implemented.

btol

bound on the linear predictor to bound the searching space.

log.alpha.bound

bound for the log of the parameter alpha.

Value

• coefficients
  the named vector of coefficients.
• alpha
  the phylogenetic correlation parameter.
• sd
  standard deviation for the regression coefficients, given the phylogenetic correlation parameter.
• vcov
  covariance matrix for the regression coefficients, given the phylogenetic correlation parameter.
• y
  response.
• n
  number of observations (tips in the tree).
• d
  number of dependent variables.
• formula
  the model formula.
• call
  the original call to the function.
• model
  the phylogenetic model for the covariance.

encoding

latin1

Details

This function uses an algorithm that is linear in the number of tips in the tree.

References

Ho, L. S. T. and An�, C. "A linear-time algorithm for Gaussian and non-Gaussian trait evolution models". Systematic Biology in review.

Ives, A. R. and T. Garland, Jr. 2010. "Phylogenetic logistic regression for binary dependent variables". Systematic Biology 59:9-26.

Examples

set.seed(123456)
tre = rtree(50)
x = rTrait(phy=tre)
X = cbind(rep(1,50),x)
y = rbinTrait(phy=tre, beta=c(-1,0.5), alpha=1 ,X=X)
dat = data.frame(trait01 = y, predictor = x)
fit = phyloglm(trait01~predictor,phy=tre,data=dat)
summary(fit)
coef(fit)
vcov(fit)