CIetterson | R Documentation |
Calculates the Monte Carlo confidence intervals for the estimated carcass detection probability when persistence probability and searcher efficiency are uncertain.
CIetterson(s, s.lwr, s.upr, f, f.lwr, f.upr, J, s.time.variance = "carcass age",
f.time.variance = "number of searches", nsim = 1000, ci = 0.95)
s |
point estiate for persistence probability (see help file for functions etterson14, ettersonEq14v1 or ettersonEq14v2) |
s.lwr |
lower limit of the 95% confidence interval of persistence probability |
s.upr |
upper limit of the 95% confidence interval of persistence probability |
f |
point estimate for the searcher efficiency (see help file for functions etterson14, ettersonEq14v1 or ettersonEq14v2 |
f.lwr |
lower limit of the 95% confidence interval of searcher efficiency |
f.upr |
upper limit of the 95% confidence interval of searcher efficiency |
J |
vector of search intervals |
s.time.variance |
character, one of "date" or "carcass age" |
f.time.variance |
character, one of "date" or "number of searches" |
nsim |
number of Monte Carlo simulations |
ci |
size of the confidence interval, default is 0.95 |
The time variance in s and f is either both with date or both with carcass age and number of searches, respectively. In case of constant s and f, the function uses ettersonEq14 independent of the arguments s.time.variance or f.time.variance, when only one value is given for both parameters.
a list
p.lower |
lower limit of the confidence interval |
p.upper |
upper limit of the confidence interval |
F. Korner
J <- c(2,3,2,4,3,5,3,2,3,4)
s <- plogis(seq(0.2, 2, length=sum(J)))
f <- plogis(seq(1.5, 0.9, length=length(J)))
s.lwr<- plogis(seq(0.2, 2, length=sum(J))-0.5)
f.lwr <- plogis(seq(1.5, 0.9, length=length(J))-0.3)
s.upr <- plogis(seq(0.2, 2, length=sum(J))+0.5)
f.upr <- plogis(seq(1.5, 0.9, length=length(J))+0.3)
CIetterson(s=s, s.lwr=s.lwr, s.upr=s.upr, f=f, f.lwr=f.lwr, f.upr=f.upr, J=J, nsim=100)
# nsim is too low, please, increase!
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