paleoTS (version 0.4-4)

LRI: Log-Rate, Log-Interval (LRI) method of Gingerich

Description

Gingerich (1993) introduced a method that plots on log-log scale, the rate and interval for each pair of samples in an evolutionary sequence. On this plot, the slope is interpreted as an indicator of evolutionary mode (-1 for stasis, 0.5 for random walk, 0 for directional), and the intercept is interpreted as a measur of the rate of evolution over one generation.

Usage

LRI(x, gen.per.t = 1e+06, draw = TRUE)

Arguments

x

a paleoTS object

gen.per.t

the number of generations per unit time (e.g., 1e6 for yearly generations and time in x is in Myr)

draw

logical, if TRUE, a plot is produced

Value

• A named vector of three elements: Intercept, slope and GenerationalRate

Details

Following Gingerich (1993), a robust line is fit through the points by minimizing the sum of absolute deviations.

References

Gingerich, P.D. 1993. Quantification and comparison of evolutionary rates. American Journal of Science 293-A:453--478. Gingerich, P.D. 2009. Rates of evolution. Annual Review of Ecology Evolution and Systematics 40:657--675.

See Also

fit3models

Examples

xFast<- sim.GRW(ns=20, ms=0.5, vs=0.2)   # fast evolution
	xSlow<- sim.Stasis(ns=20, theta=10, omega=0)   # strict stasis! rates are actually zero
	wFast<- LRI(xFast, draw=FALSE)
	wSlow<- LRI(xSlow, draw=FALSE)
	## LRI usually assigns faster generational rate to Strict Stasis!
	print(wFast[3],4)
	print(wSlow[3],4)