estimate_ehat_variance {AnglerCreelSurveySimulation} | R Documentation |
Calculate within-day variance of estimated effort (Ehat)
Description
This function multiple outputs from simulate_bus_route
to estimate the variance in estimated effort, .
Usage
estimate_ehat_variance(data)
Arguments
data |
A dataframe of output from |
Details
The variance in is estimated from multiple simulated surveys
on a single theoretical day (Within-day variance of
. The variance is estimated by
where is the total estimated party hours for an individual survey
(i.e.,
), and
is the mean of the
,
and n is how many simulations were run. The equation above matches the variables
used in Jones et al. (1990).
Jones et al. (1990) stated that estimating within-day variance would require several crews conducting two or more randomized surveys along a given route on the same day. They use this conservative estimator of variance for building confidence intervals around the estimates of effort.
Value
The variance in estimated effort, Ehat
(), from Robson
and Jones (1989) and Jones et al. (1990).
Author(s)
Steven H. Ranney
References
Jones, C. M., D. Robson, D. Otis, S. Gloss. 1990. Use of a computer model to determine the behavior of a new survey estimator of recreational angling. Transactions of the American Fisheries Society 119:41-54.
Robson, D., and C. M. Jones. 1989. The theoretical basis of an access site angler survey design. Biometrics 45:83-98.
Examples
#Set up a simulation to run repeatedly
## Not run:
start_time = c(0, 1.5)
wait_time = c(1, 6.5)
fishing_day_length <- 12
n_anglers = c(50, 300)
n_sites = 2
sampling_prob <- sum(wait_time)/fishing_day_length
mean_catch_rate <- 2.5
# Simulate the creel survey n times
times <- 100
sims <-
matrix(data = NA, nrow = times, ncol = 5) %>%
as.data.frame()
names(sims) = c("Ehat", "catch_rate_ROM", "true_catch", "true_effort", "mean_lambda")
for(i in 1:times){
sims[i, ] <- simulate_bus_route(start_time, wait_time, n_anglers, n_sites,
sampling_prob, mean_catch_rate)
}
estimate_ehat_variance(sims)
## End(Not run)