| extCDF {popbio} | R Documentation |
Returns the extinction time cumulative distribution function using parameters derived from population counts.
extCDF(mu, sig2, Nc, Ne, tmax = 50)
mu |
estimated value of mean mu |
sig2 |
estimated value of sample variance |
Nc |
current population size |
Ne |
quasi-extinction threshold |
tmax |
latest time to calculate extinction probability, default 50 |
A vector with the cumulative probabilities of quasi-extinction from t=0 to t=tmax.
Chris Stubben
converted Matlab code from Box 3.3 and equation 3.5 in Morris and Doak (2002)
Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA.
countCDFxt for bootstrap confidence intervals
data(grizzly)
logN<-log(grizzly$N[-1]/grizzly$N[-39])
mu<-mean(logN)
sig2<-var(logN)
## grizzly cdf (log scale)
ex<-extCDF(mu, sig2, Nc=99, Ne=20)
plot(ex, log='y', type='l', pch=16, col="blue", yaxt='n',
xlab="Years", ylab="Quasi-extinction probability",
main="Yellowstone Grizzly bears")
pwrs<-seq(-15,-5,5)
axis(2, at = 10^pwrs, labels=parse(text=paste("10^", pwrs, sep = "")),
las=1)
##plot like fig 3.10 (p 90)
n<-seq(20, 100, 2)
exts<-numeric(length(n))
for (i in 1:length(n) )
{
ex<-extCDF(mu, sig2, Nc=n[i], Ne=20)
exts[i]<-ex[50]
}
plot(n, exts, type='l', las=1,
xlab="Current population size",
ylab="Probability of quasi-extinction by year 50",
main="Quasi-extinction depends on population size")