Calculates minimum sample size for one sampling event in a Petersen mark-recapture experiment, given the sample size in the other event and an best guess at true abundance.
n2RR(
N,
n1,
conf = c(0.99, 0.95, 0.9, 0.85, 0.8, 0.75),
acc = c(0.5, 0.25, 0.2, 0.15, 0.1, 0.05, 0.01)
)The best guess at true abundance
The size of the first (or second) sampling event
A vector of the desired levels of confidence to investigate.
Allowed values are any of c(0.99,0.95,0.9,0.85,0.8,0.75). Defaults to
all of c(0.99,0.95,0.85,0.8,0.75).
A vector of the desired levels of relative accuracy to
investigate. Allowed values are any of
c(0.5,0.25,0.2,0.15,0.1,0.05,0.01). Defaults to all of
c(0.5,0.25,0.2,0.15,0.1,0.05,0.01).
A list of minimum sample sizes. Each list element corresponds to a unique level of confidence, and is defined as a data frame with each row corresponding to a unique value of relative accuracy. Two minimum sample sizes are given: one calculated from the sample size provided for the other event, and the other calculated under n1=n2, the most efficient scenario.
Robson, D. S., and H. A. Regier. 1964. Sample size in Petersen mark-recapture experiments. Transactions of the American FisheriesSociety 93:215-226.
# NOT RUN {
n2RR(N=1000, n1=100)
# }
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