assess.accuracy: Function to assess the accuracy criterion for CPUE and...

In jBernardADFG/LakeLouiseBurbotOP2020: Functions used in the 2020 Lake Louise OP

Description

Function to assess the accuracy criterion for CPUE and abundance

Usage

assess.accuracy(ts_mat, N_vec, sig_vec, q_bar, sd_q, acc_lev, A, n_mc = 100)

Arguments

ts_mat	A matrix specifying the transect/set arrangement. Columns represent transects while rows represent sets. Eg: cbind(c(T,T,T,F),c(T,T,F,F),c(T,T,T,T))
N_vec	A numerical vector specifying the "true" mean abundance
sig_vec	A numerical vector specifying the between transect log scale standard deviation
q_bar	The estimate of the catchability coefficient
sd_q	An estimate of the standard deviation of the catchability coefficient
acc_lev	A vector of length two giving the prescribed levels of accuracy for CPUE and N respectively.
A	The area of the lake (in XX)
n_mc	The number of times to run the Monte Carlo simulation

Value

Returns a matrix giving the percentage of the time that the estimate is within acc_lev percent of the true value. The rows of the matrix coorespond to the entries in N_vec while the columns coorespond to entries in sig_vec.

Examples

load("S:/Jordy/louiseOP2020/Data/lakelines.Rdata") # Load Lake Louise lakelines
n_max <- 492
ts_mat <- pick.coords(lakelines, n_max)$ts_mat
N_vec <- seq(1000, 10000, by=1000) 
sig_vec <- seq(.1, 1, by=.1)
q_bar <- 0.6478999
sd_q <- 0.07966257
A <- 6519
acc_lev <- c(0.3, 0.3)
assess.accuracy(ts_mat, N_vec, sig_vec, q_bar, sd_q, acc_lev, A)

jBernardADFG/LakeLouiseBurbotOP2020 documentation built on March 25, 2020, 12:06 a.m.