paleoTS (version 0.5-1)

lynchD: Compute rate metric from Lynch (1990)

Description

This function computes D, the rate metric proposed by Lynch (1990). This metric derives from the random walk model, with D = Vstep/(2Vp), where Vstep is the step variance of the unbiased random walk, and Vp is the within sample variance, pooled among samples. Under mutation - drift equilibrium, D is expected to range approximately between 5e-5 and 5e-3.

Usage

lynchD(y, gen.per.t = 1e+06, pool = TRUE, method=c('Joint', 'AD'), ...)

Arguments

y

a paleoTS object

gen.per.t

the number of generations per unit time

pool

logical, if the variance should be pooled across samples in estimating Vstep

method

parameterization to use: based on ancestor-descendant (AD) differences, or on Joint consideration of all samples

…

further arguments, passed to opt.URW or opt.joint.URW

Value

D

value of rate metric

pooled.var

value of pooled within-sample variance

gen.per.t

number of generations per unit time

vstep

computed Vstep, at the original time scale of y

drift.range

exepcted minimum and maximum values of D consistent with neutral evoltuion

result

conclusion reached about the plausibility of neutral evolution

Details

The gen.per.t argument indicates the number of organismal generations for each unit of time with which the time-series y was measured. For example, is y$tt is measured in millions of years, and the species has annual generations, gen.per.t would be 1e6. For difference between the method choices, see Hunt (2008).

Estimation of Vstep is done on the original time scale of y, and then the values are converted to generational time scales using gen.per.t. This is for numerical reasons, as it avoids computations on possible very low numbers.

References

Lynch, M. 1990. The rate of morphological evolution in mammals from the standpoint of the neutral expectation. The American Naturalist 136:727--741. Hunt, G. 2008. Evolutionary patterns within fossil lineages: model-based assessment of modes, rates, punctuations and process.. In R.K. Bambach and P.H. Kelley, eds. From Evolution to Geobiology: Research Questions Driving Paleontology at the Start of a New Century:578--601. Hunt, G. 2012. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology 38:351--373.

See Also

opt.URW

Examples

# NOT RUN {
 y<- sim.GRW(ns=20, ms=0, vs=1e-4, tt=seq(0,1e6, length.out=20))  # per-year simulation
 lynchD(y, gen.per.t=1)		# 1 generation per year
# }