Description Usage Arguments Details Value See Also Examples
The function filters out all the unobserved information from a ‘sample.pt’ object, leaving only the observed data. It is useful when creating sample.pt objects for exercises – when you don't want those doing the exercises to be able to see the whole population.
1 2 | obscure(sample)
obscure.sample.pt(sample)
|
sample |
Point transect sample object (of class ‘sample.pt’). |
This function removes from the ‘sample.pt’ object all data relating to animals and groups that were not detected – those for which ‘(sample$detected!=T | !is.na(sample$detected))’.
obscure.sample.pt
returns an object of class 'sample.pt´ which has the following
elements:
population |
object of class 'population´, but containing only data for observed members of the population. |
design |
object of class 'design.pt´. |
detected |
vector indicating which animal groups have been detected. |
distance |
vector of perpendicular distances of detected animal groups inside the survey units from the respective points. |
transect |
vector of point numbers from which animal groups were detected. |
generate.sample.pt
, setpars.survey.pt
, summary.sample.pt
,
plot.sample.pt
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # First generate a population and sample it:
myreg<-generate.region(x.length = 50, y.width = 80)
mydens <- generate.density()
mypoppars<-setpars.population(myreg, density.pop = mydens,
number.groups = 500, 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)
mypop<-generate.population(mypoppars)
mydespars<-setpars.design.pt(myreg, n.transects = 4, n.units = 20, visual.range = 2.5)
set.seed(1066)
mydes<-generate.design.pt(mydespars)
mysurvpars<-setpars.survey.pt(mypop, mydes, disthalf.min = 1.5, disthalf.max = 2)
mysamp<-generate.sample.pt(mysurvpars)
plot(mysamp,whole.population=T)
summary(mysamp)
# now strip the unobserved data out of the sample.pt object:
obs.samp<-obscure(mysamp)
plot(obs.samp,whole.population=T)
# note that `whole.population=T' has no effect - because all unobserved data is gone
summary(obs.samp)
# ... but the summary is the same - because summary involves only the observed data
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.