rate.estimate {geiger} | R Documentation |
Uses Magellon and Sanderson method to calculate net diversification rate for a clade given extant diversity and age Can 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
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))
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 |
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
Luke J. Harmon
Magallon and Sanderson 2000
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)