countCDFxt: Count-based extinction probabilities and bootstrap confidence...

In popbio: Construction and Analysis of Matrix Population Models

Count-based extinction probabilities and bootstrap confidence intervals

Description

This function takes parameters derived from population counts and calculates the probability of extinction with bootstrap confidence intervals for a density-independent model, using a diffusion approximation.

Usage

countCDFxt(mu, sig2, nt, Nc, Ne, tq = nt, tmax = 50, Nboot = 500, plot = TRUE)

Arguments

mu	estimated value of mean mu
sig2	estimated value of sample variance
nt	number of transitions in the data set
Nc	current population size
Ne	quasi-extinction threshold
tq	length of the census (in years), default is number of transitions
tmax	latest time to calculate extinction probability, default 50
Nboot	number of bootstrap samples for calculating confidence intervals for extinction probabilities, default 500)
plot	draw extinction time CDF plot with log-scale on y-axis

Details

converted Matlab code from Box 3.4 in Morris and Doak (2002)

Value

The function plots the cumulative probabilities of quasi-extinction through time with 95% confidence intervals. It also returns a data frame with the extinction time CDF for the best parameter estimates (Gbest), and the lower and upper bootstrap confidence limits for extinction probabilites (Glo, Gup).

Author(s)

Adapted to R by Patrick Nantel, 4 May 2005, from program 'extprob' of Morris and Doak (2002: 79-86)

References

Dennis et al. 1991, Ecological Monographs 61: 115-143

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

See Also

extCDF

Examples

## plot like Figure 3.8 in Morris and Doak (2002).
logN <- log(grizzly$N[-1]/grizzly$N[-39])
countCDFxt(mu=mean(logN), sig2=var(logN), nt=38, tq=38, Nc=99, Ne=20)

popbio documentation built on May 29, 2024, 4:35 a.m.