# extCDF: Count-based extinction time cumulative distribution function In popbio: Construction and Analysis of Matrix Population Models

## Description

Returns the extinction time cumulative distribution function using parameters derived from population counts.

## Usage

 1 extCDF(mu, sig2, Nc, Ne, tmax = 50)

## Arguments

 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

## Value

A vector with the cumulative probabilities of quasi-extinction from t=0 to t=tmax.

Chris Stubben

## Source

converted Matlab code from Box 3.3 and equation 3.5 in Morris and Doak (2002)

## References

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

## Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 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")

### Example output

Warning message:
In xy.coords(x, y, xlabel, ylabel, log) :
2 y values <= 0 omitted from logarithmic plot

popbio documentation built on May 4, 2018, 1:04 a.m.