freqdep {learnPopGen}

Numerical analysis of a frequency dependent seletion model

Description

This function performs numerical analysis of a frequency dependent selection model based on Rice (2004; Evolutionary Theory: Mathematical & Conceptual Foundations). The fitnesses of the three genotypes in the model are as follows, where f(XX) denotes the frequency of the XX genotype: w(AA)=1-3*f(Aa)+3*f(aa); w(Aa)=1-s*f(Aa); and w(aa)=1-3*f(Aa)+3*f(AA). As shown in Rice (2004), though entirely deterministic, the model can exhibit chaotic behavior under some values for s.

Usage

	freqdep(p0=0.01, s=0, time=100, show="p", pause=0, ...)

Arguments

p0

Starting frequency for the A allele.

s

Parameter that determines the strength of selection against heterozygotes when they are common.

time

Number of generations to run the analysis.

show

Various options for plotting. "p" shows the frequency of A through time; "q" gives the frequency of the a allele; "fitness" gives the mean population fitness through time; "surface" plots the mean fitness as a function of p; "deltap" shows the change in p as a function of p; "cobweb" creates a cobweb plot showing p(t) by p(t+1). The default is show="p".

pause

Pause between generations. pause=0.01 (for instance) might smooth animation.

...

optional arguments. Presently, the only optional argument in freqdep is color, which can be used to change the color of the lines of the plot. The plot method can also accept the optional arguments type (e.g., "l" or "s") and lwd.

Value

The function creates one of several possible plots, depending on the value of show.

The use of cobweb plots follows selection.

The function also invisibly returns an object of class "freqdep" containing the frequency of the allele A through time, if this was calculated by the selected method. This can be printed or plotted using the corresponding methods. (See examples.)

Author(s)

Liam Revell [e-mail]

See Also

sexratio

Examples

	freqdep(time=100)
	freqdep(s=1.5,time=100)
	p<-freqdep(s=2,show="cobweb",time=100)
	plot(p)