Description Usage Arguments Details Value Note Author(s) See Also Examples
Create an object of class ext.risk
.
1 | ext.risk(extrisk, year, nboot, ext.boot, alpha, ext.ci, model.type, model.params)
|
extrisk |
The cumulative probability of quasi-extinction projected at various times in the future |
year |
The times associated with the risks in |
nboot |
Number of bootstrap replicates used to calculate the confidence intervals |
ext.boot |
Extinction risk curves for each of the bootstrap replicates |
alpha |
One minus the confidence level |
ext.ci |
Confidence intervals of cumulative extinction risk |
model.type |
Name of the model used to perform the PVA |
model.params |
Estimated parameters of the model used to perform the PVA |
If extrisk
and year
are vectors of length n, then ext.boot
has dimension
(n, nboot)
and ext.ci
has dimension (n, 2)
. Each column
of ext.boot
represents a single bootstrap replicate.
If there are no bootstrap replicates, set nboot, ext.boot, alpha
, and
ext.ci
all to NULL
.
An object of class ext.risk
This function was developed in order to document the ext.risk
class. In the
normal course of events, there should be no need for the user to call this
function.
Bruce E. Kendall (kendall@bren.ucsb.edu)
print.ext.risk
and plot.ext.risk
for printing and
plotting ext.risk
objects; these objects are generated, for example,
by count.DI.PVA
1 2 3 4 5 6 7 8 9 10 | ## Load the grizzly bear data and run a DI PVA
data(grizzly)
grizzly.ext <- count.DI.PVA(grizzly$N, Nx=20, Nc=50, nboot=1000)
## Print the confidence intervals for all 100 years
cbind(grizzly.ext$year, grizzly.ext$ext.ci)
## Plot a selection of bootstrap replicates
matplot(grizzly.ext$year, grizzly.ext$ext.boot[,1:100], type='l', col='black',
lty=1, xlab="Year", ylab="Cumulative extinction probability")
|
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