Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(AnglerCreelSurveySimulation)
anglers <- make_anglers(n_anglers = 100, mean_trip_length = 3.5, fishing_day_length = 12)
## -----------------------------------------------------------------------------
head(anglers)
## ----warning = FALSE----------------------------------------------------------
library(dplyr)
library(ggplot2)
# Histogram overlaid with kernel density curve
anglers %>%
ggplot(aes(x=trip_length)) +
geom_histogram(aes(y=..density..),
binwidth=.1,
colour="black", fill="white") +
geom_density(alpha=.2, fill="#FF6666")
## -----------------------------------------------------------------------------
anglers %>%
get_total_values(start_time = 0, wait_time = 8, sampling_prob = 8/12, mean_catch_rate = 2.5)
## -----------------------------------------------------------------------------
sim <- simulate_bus_route(start_time = 0, wait_time = 8, n_sites = 1, n_anglers = 100,
sampling_prob = 8/12, mean_catch_rate = 2.5, fishing_day_length = 12)
sim
## -----------------------------------------------------------------------------
sim <- conduct_multiple_surveys(n_sims = 20, start_time = 0, wait_time = 8, n_sites = 1,
n_anglers = 100, sampling_prob = 8/12,
mean_catch_rate = 2.5, fishing_day_length = 12)
sim
## -----------------------------------------------------------------------------
mod <-
sim %>%
lm((Ehat * catch_rate_ROM) ~ true_catch, data = .)
summary(mod)
## -----------------------------------------------------------------------------
#Create a new vector of the estimated effort multiplied by estimated catch rate
sim <-
sim %>%
mutate(est_catch = Ehat * catch_rate_ROM)
sim %>%
ggplot(aes(x = true_catch, y = est_catch)) +
geom_point() +
geom_abline(intercept = mod$coefficients[1], slope = mod$coefficients[2],
colour = "red", size = 1.01)
## -----------------------------------------------------------------------------
mod <-
sim %>%
lm(Ehat ~ true_effort, data = .)
summary(mod)
#Create a new vector of the estimated effort multiplied by estimated catch rate
sim %>%
ggplot(aes(x = true_effort, y = Ehat)) +
geom_point() +
geom_abline(intercept = mod$coefficients[1], slope = mod$coefficients[2],
colour = "red", size = 1.01)
## -----------------------------------------------------------------------------
start_time <- 0
wait_time <- 12
sampling_prob <- 1
sim <- conduct_multiple_surveys(n_sims = 20, start_time = start_time, wait_time = wait_time,
n_sites = 1, n_anglers = 100, sampling_prob = 1,
mean_catch_rate = 2.5, fishing_day_length = 12)
sim
## ----echo = FALSE-------------------------------------------------------------
mod <-
sim %>%
lm(Ehat ~ true_effort, data = .)
summary(mod)
sim %>%
ggplot(aes(x = true_effort, y = Ehat)) +
geom_point() +
geom_abline(intercept = mod$coefficients[1], slope = mod$coefficients[2],
colour = "red", size = 1.01)
## -----------------------------------------------------------------------------
start_time <- c(0, 4.5)
wait_time <- c(4, 3.5)
n_sites = 2
n_anglers <- c(50, 50)
fishing_day_length <- 12
sampling_prob <- sum(wait_time)/fishing_day_length
sim <- conduct_multiple_surveys(n_sims = 20, start_time = start_time, wait_time = wait_time,
n_sites = n_sites, n_anglers = n_anglers,
sampling_prob = sampling_prob, mean_catch_rate = 2.5,
fishing_day_length = fishing_day_length)
sim
## ----echo = FALSE-------------------------------------------------------------
mod <-
sim %>%
lm(Ehat ~ true_effort, data = .)
summary(mod)
sim %>%
ggplot(aes(x = true_effort, y = Ehat)) +
geom_point() +
geom_abline(intercept = mod$coefficients[1], slope = mod$coefficients[2],
colour = "red", size = 1.01)
## -----------------------------------------------------------------------------
#Weekend clerks
start_time_w <- 2
wait_time_w <- 10
n_sites <- 1
n_anglers_w <- 75
fishing_day_length <- 12
sampling_prob <- 8/12
sim_w <- conduct_multiple_surveys(n_sims = 8, start_time = start_time_w,
wait_time = wait_time_w, n_sites = n_sites,
n_anglers = n_anglers_w, sampling_prob = sampling_prob,
mean_catch_rate = 2.5, fishing_day_length = fishing_day_length)
sim_w
#Add the weekday survey and weekend surveys to the same data frame
mon_survey <-
sim_w %>%
bind_rows(sim)
mod <-
mon_survey %>%
lm(Ehat ~ true_effort, data = .)
summary(mod)
## ----echo = FALSE-------------------------------------------------------------
mon_survey %>%
ggplot(aes(x = true_effort, y = Ehat)) +
geom_point() +
geom_abline(intercept = mod$coefficients[1], slope = mod$coefficients[2],
colour = "red", size = 1.01)
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