sim.drift.selection: Simulate drift and selection
In nicholsonppp: Evolution simulation and classification

Simulate allele frequency evolution in several populations according to a simple drift and selection model.

sim.drift.selection(populations = 12, popsize = 1000, generations = 50, loci.per.s.value = 10, beta1 = 0.7, beta2 = 0.7, p.neutral = 0.8, s = c(1, 5)/100, adapt.pop = c(blue = 0.4, red = 0.4, neutral = 0.2), array.fun = array)

`populations`	Number of populations.
`popsize`	Size of simulated populations. Vectors smaller than number of populations will be repeated.
`generations`	Generations of evolution to simulate.
`loci.per.s.value`	Number of loci simulated for each s value.
`beta1`	Parameter for beta distribution of initial allele frequencies.
`beta2`	Parameter for beta distribution of initial allele frequencies.
`p.neutral`	Proportion of neutral alleles to simulate.
`s`	Vector of selection strength values to simulate.
`adapt.pop`	Probabilities of color adaptation in populations.
`array.fun`	Function to use to construct the evolution array. By default we use a normal R array, but this can be any function that accepts data as the first argument, and a dim argument, and gives a result that behaves like an array. In particular you can use the ff function from the ff package if the simulation is too large for memory.