View source: R/stoch.quasi.ext.R
| stoch.quasi.ext | R Documentation | 
Estimate the quasi-extinction probability by simulation for a structured population in an an independently and identically distributed stochastic environment
stoch.quasi.ext(
  matrices,
  n0,
  Nx,
  tmax = 50,
  maxruns = 10,
  nreps = 5000,
  prob = NULL,
  sumweight = NULL,
  verbose = TRUE
)
| matrices | a  | 
| n0 | initial population vector | 
| Nx | quasi-extinction threshold | 
| tmax | number of time steps or projection intervals | 
| maxruns | number of times to simulate cumulative distribution function | 
| nreps | number of iterations | 
| prob | a vector of probability weights used by  | 
| sumweight | A vector of ones and zeros used to omit stage classes when checking quasi-extinction threshold. Default is to sum across all stage classes | 
| verbose | Print comment at start of run 1,2,3,etc. | 
converted Matlab code from Box 7.5 in Morris and Doak (2002)
A matrix with quasi-extinction probabilities for each run by columns
Chris Stubben
Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA.
stoch.projection
n <- c(4264, 3,30,16,25,5)
names(n) <- c("seed",  "seedlings", "tiny", "small", "medium" , "large")
## exclude seeds using sumweight.  Using 100 nreps for speed
x <- stoch.quasi.ext(hudsonia, n, Nx=10, nreps=100, sumweight=c(0,1,1,1,1,1))
matplot(x, xlab="Years", ylab="Quasi-extinction probability",
 type='l', lty=1, las=1,
 main="Time to reach a quasi-extinction threshold
of 10 above-ground individuals")
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