Description Usage Arguments Value See Also Examples
This function calculates confidence intervals for group abundance for the plot sampling method.
1 2 |
samp |
object of class 'sample.pl´. |
HT |
if FALSE, the abundance estimate produced is the MLE, if TRUE it is the Horvitz-Thompson estimate. |
vlevels |
vector of percentage levels for confidence interval. |
ci.type |
method for constructing the confidence interval. Possible methods are * 'normal´ for a CI based on assumed normality of the estimator, * 'boot.par´ for a parametric bootstrap CI, * 'boot.nonpar´ for a nonparametric bootstrap CI. |
nboot |
number of bootstrap replications. |
plot |
if true the distribution of the estimator of N is to be plotted. |
seed |
the number passed to set.seed() to initialise random number generator |
... |
other plot parameters |
An object of class 'int.est.pl´ containing the following items:
levels |
percentage levels for confidence interval |
ci |
the confidence interval |
boot.mean |
mean of bootstrap estimates |
boot.dbn |
full set of nboot bootstrap estimates. |
generate.sample.pl
, point.est.pl
summary.sample.pl
, plot.sample.pl
set.seed
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | pl.reg <- generate.region(x.length = 100, y.width = 50)
pl.dens <- generate.density(pl.reg)
pl.poppars<-setpars.population(density.pop=pl.dens, number.groups = 100, size.method = "poisson",
size.min = 1, size.max = 5, size.mean = 1, exposure.method = "beta", exposure.min = 2,
exposure.max = 10, exposure.mean = 6, exposure.shape = 1)
pl.pop <- generate.population(pl.poppars, seed=456)
pl.despars<-setpars.design.pl(pl.reg, n.interval.x = 10, n.interval.y = 20,method = "random", area.covered = 0.2)
pl.des <- generate.design.pl(pl.despars, seed=789)
pl.samp<-generate.sample.pl(pl.pop, pl.des, seed=101112)
# normal-based CI
pl.int.est.norm<-int.est.pl(pl.samp, vlevels = c(0.025, 0.975), ci.type = "normal", nboot = 99, plot = T, seed=1)
summary(pl.int.est.norm)
plot(pl.int.est.norm)
# parametric bootstrap
pl.int.est.pbs<-int.est.pl(pl.samp, vlevels = c(0.025, 0.975), ci.type = "boot.par", nboot = 99, plot = F, seed=NULL)
summary(pl.int.est.pbs)
plot(pl.int.est.pbs, nclass=20)
# nonparametric bootstrap
pl.int.est.npbs<-int.est.pl(pl.samp, vlevels = c(0.025, 0.975), ci.type = "boot.nonpar", nboot = 99, plot = F, seed=3)
summary(pl.int.est.npbs)
plot(pl.int.est.npbs)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.