multiresultm: Incorporate demographic stochasticity into population...
In popbio: Construction and Analysis of Matrix Population Models

Description Usage Arguments Details Value Author(s) References Examples

Generates multinomial random numbers for state transitions and lognormal or binomial (for clutch size=1) random numbers for fertilities and returns a vector of the number of individuals per stage class at t+1.

1	multiresultm(n, T, F, varF = NULL)

`n`	the vector of numbers of individuals per class at t
`T`	a transition T matrix
`F`	a fertility F matrix
`varF`	a matrix of inter-individual variance in fertilities, default is NULL for simulating population where clutch size = 1, so that fertilities give the probabilities of birth

Adapted from Matlab code in Box 8.11 in Morris and Doak (2002) and section 15.1.3 in Caswell (2001)

a vector of the number of individuals per class at t+1.

Patrick Nantel

Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation, Second edition. Sinauer, Sunderland, Massachusetts, USA.

Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA.

x <- splitA(whale)
whaleT <- x$T
whaleF <- x$F
multiresultm(c(1,9,9,9),whaleT, whaleF)
multiresultm(c(1,9,9,9),whaleT, whaleF)
## create graph similar to Fig 15.3 a
reps <- 10    # number of trajectories
tmax <- 200   # length of the trajectories
totalpop <- matrix(0,tmax,reps)  # initializes totalpop matrix to store trajectories
nzero <- c(1,1,1,1) # starting population size
for (j in 1:reps) {
   n <- nzero
   for (i in 1:tmax) {
      n <- multiresultm(n,whaleT,whaleF)
      totalpop[i,j] <- sum(n)
   }
}
matplot(totalpop, type = 'l', log="y",
        xlab = 'Time (years)', ylab = 'Total population')