Description Usage Arguments Details Value See Also Examples
The function filters out all the unobserved information from a ‘sample.pl’ object, leaving only the observed data. It is useful when creating ‘sample.pl’ objects for exercises – when you don't want those doing the exercises to be able to see the whole population.
1 | obscure(sample)
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samp |
Plot sampling method object, of class 'sample.pl´. |
This function removes from the ‘sample.pl’ object all data relating to animals and groups that were not detected – those for which ‘(sample$detected!=T | !is.na(sample$detected))’.
obscure.sample.pl
returns an object of class 'sample.pl´ which has the following elements:
population |
object of class 'population´. |
design |
object of class 'design.pl´. |
detected |
vector indicating which animal groups have been detected. |
unit |
vector indicating survey units in which animal groups were detected. |
parents |
Details of WiSP objects passed to function |
created |
Creation date and time |
generate.sample.pl
, summary.sample.pl
plot.sample.pl
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | reg <- generate.region(x.length = 50, y.width = 80)
dens <- generate.density(reg)
pop.pars<-setpars.population(reg, density.pop = 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)
pop <- generate.population(pop.pars)
pl.des.pars<-setpars.design.pl(reg, n.interval.x = 5, n.interval.y = 6, method = "regular", area.covered = 0.18, jitter = "unsync")
pl.des <- generate.design.pl(pl.des.pars)
pl.samp <- generate.sample.pl(pop, pl.des)
obs.pl.samp<-obscure.sample.pl(pl.samp)
# Note that whole.population=T has no effect on obscured sample:
plot(pl.samp, whole.population=T)
plot(obs.pl.samp, whole.population=T)
# ... but summary is the same:
summary(pl.samp)
summary(obs.pl.samp)
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