Estimate regression coefficients for tip species curves

Description

Estiamtes regression coefficients for tip species curves from raw data. May be useful if wanting to perform methods without first performing ancestral curve reconstruction via the phylocurve() function.

Usage

1
2
get.tip.coefficients(formula, tree, data, ymin = 0.01, ymax = 0.99,
ylength = 30, species.identifier = "species", verbose = FALSE)

Arguments

formula

Formula for function-valued trait (currently only supports models of the form Y~X)

tree

A phylogenetic tree of class "phylo"

data

A data frame with data for tip curve estimation, where each row contains a single data point. A column named "species" has the species names corresponding to each data point, a predictor (X) variable and the response (Y) variable, which must be scaled between 0 and 1.

ymin

Because 0 and 1 are undefined for inverse logit functions, the minimum and maximum values are defaulted to .01 and .99. Can be adjusted as needed.

ymax

Because 0 and 1 are undefined for inverse logit functions, the minimum and maximum values are defaulted to .01 and .99. Can be adjusted as needed.

ylength

How many landmarks (points on the curve) to evaluate.

species.identifier

Default is "species". Can be changed if the column in data has a different species identifier name.

verbose

ether to print progress during tip curve coefficient estimation.

Value

Estimated regression coefficients of tip curves.

Examples

1
2
3
4
5
6
7
8
9
# simulate evolution of a function-valued trait (glm with logit link)
sim_data <- sim.curves()

# get tip coefficients and aligned function data
tip.coefficients <- get.tip.coefficients(formula = y~x,tree = sim_data$tree,data = sim_data$data)
data <- get.aligned.function.data(tip.coefficients)

# estimate evolutionary rates
evo.model.fitted <- evo.model(sim_data$tree,data)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.