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geiger (version 1.0-91)

rate.estimate: Calculate net diversification rate with confindence limits, and test diversities

Description

rate.estimate Uses Magellon and Sanderson method to calculate net diversification rate for a clade given extant diversity and age. Associated functions crown.p and stem.p also calculate the probability of obtaining a clade with at least k species given a net diversification rate (r), extinction fraction (e), and time interval. Associated functions stem.limits and crown.limits generate confidence limits on extant diversity given a net diversification rate (r), extinction fraction (e), and time interval.

Usage

rate.estimate(time=0, n=0, phy=NULL, epsilon = 0, missing = 0, crown=TRUE, kendall.moran=FALSE)
crown.p(time, r, epsilon, n)
stem.p(time, r, epsilon, n)
crown.limits(r, epsilon, time, prob=c(0.025, 0.975))
stem.limits(r, epsilon, time, prob=c(0.025, 0.975))

Arguments

time
Time interval; can be a vector
n
Number of extant species
phy
Phylogenetic tree; can be supplied instead of time and n. If you're using a tree then crown is automatically true.
epsilon
Extinction rate as a fraction of speciation rate
missing
Number of taxa missing from tree
crown
If true, time is treated as crown age; otherwise, stem age
kendall.moran
If true, calculates Kendall-Moran estimate of speciation rate; requires a complete phylogenetic tree
r
Net diversification rate, birth - death
prob
Range of probabilities for calculating confidence region

Value

  • rate.estimate: Returns net diversification rate r = lambda - mu, and confidence interval crown.p and stem.p: Returns the probability of obtaining a clade as big as, or bigger than, size n, given time, r, and epsilon stem.limits and crown.limits: Return confidence intervals for clade size given time, r, and epsilon

References

Magallon, S. and M. J. Sanderson. 2000. Absolute diversification rates in angiosperm clades. Evolution 55:1762-1780.

Examples

Run this code
data(geospiza)
attach(geospiza)

# Assuming no extinction
rate.estimate(phy=geospiza.tree, missing=1)

# Assuming high extinction
rate.estimate(phy=geospiza.tree, epsilon=0.9, missing=1)

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