ibmpm: Metapopulation simulation
In ibmpm: Individual-based metapopulation model

Description Usage Arguments Details Value Author(s) See Also Examples

Simulate a metapopulation with genetic dynamics.

metapop(disp.mat, data, sim.len, n.offspring, carr.cap,
	event.order = c("m.disperse", "f.disperse", "mate", "reproduce"),
	pop.mod = tr.exp.growth, output.interval = NA, m.mult.mating = FALSE,
	mutation = NULL, p.mutation = 0, ...)

`disp.mat`	a square matrix of size `n.patches` x `n.patches` containing the dispersal probabilities. The source patches are given in rows, target patches in columns, so `disp.mat[i,j]` is the probability of transfer from patch `i` to patch `j`. If the rows sum to less than one, the sum gives the probability of survival during the dispersal event. On the diagonal (`disp.mat[i,i]`) are the probabilities of staying in the patch i.
`data`	a `data.frame` with columns ‘patch’, ‘sex’, and at least one additional column for allele lengths. Each row describes one individual, or, if column `n` is present it describes n individuals of the same genotype, sex, and location.
`sim.len`	numeric, the simulation length (number of time steps).
`n.offspring`	maximum number of offspring per female. This can be either a numeric scalar or vector of length `n.patches`, in the latter case values are per patch
`carr.cap`	numeric scalar or vector of length `n.patches`, carrying capacity of the patches.
`event.order`	a character vector giving the sequence of events in a single time step. Accepted values are: "m.disperse", "f.disperse", "mate" and "reproduce". The names may be abbreviated. Note that there may be multiple events of the same type.
`pop.mod`	function implementing the population model. See `pop.model`.
`output.interval`	interval at which the population state is returned (not yet inplemented).
`m.mult.mating`	logical, is multiple mating of males allowed?
`mutation`	function to carry out mutations in the 'genome' of one individual. It has to accept a numeric vector as the only argument, and return a numeric vector of the same length.
`p.mutation`	numeric scalar, the mutation probability
`...`	further arguments passed to `pop.mod`

In the data, each two homologous alleles must occur in columns next to each other, e.g. ‘allele1A’, ‘allele1B’, ‘allele2A’, ‘allele2B’, etc.

A data.frame with the same column types as the input data provided as data argument, where rows represent individuals (or genotypes/sex/location and their counts if column n was present) at time = sim.len.

patch numeric giving the patch number, referring to the row and column of disp.mat.
sex factor with two levels, "F" and "M";
n optional, number of individuals of that kind;
... remaining columns contain allele values.