plot_fitted: plot_fitted makes plots bycatch estimates (lambda of...

In eric-ward/bycatch: Fit Bayesian Models to Bycatch Data

plot_fitted makes plots bycatch estimates (lambda of Poisson), accounting for effort but not accounting for observer coverage

Description

plot_fitted makes plots bycatch estimates (lambda of Poisson), accounting for effort but not accounting for observer coverage

Usage

plot_fitted(
  fitted_model,
  xlab = "Time",
  ylab = "Events",
  include_points = FALSE,
  alpha = 0.05
)

Arguments

fitted_model	Data and fitted model returned from fit_bycatch(). If a hurdle model, then only then the plot returns the total bycatch rate (including zero and non-zero components).
xlab	X-axis label for plot
ylab	Y-axis label for plot
include_points	whether or not to include raw bycatch events on plots, defaults to FALSE
alpha	The alpha level for the credible interval, defaults to 0.05

Value

plot called from ggplot

Examples

d <- data.frame(
  "Year" = 2002:2014,
  "Takes" = c(0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0),
  "expansionRate" = c(24, 22, 14, 32, 28, 25, 30, 7, 26, 21, 22, 23, 27),
  "Sets" = c(391, 340, 330, 660, 470, 500, 330, 287, 756, 673, 532, 351, 486)
)
fit <- fit_bycatch(Takes ~ 1,
  data = d, time = "Year", effort = "Sets",
  family = "poisson", time_varying = FALSE
)
plot_fitted(fit,
  xlab = "Year", ylab = "Fleet-level bycatch",
  include_points = TRUE
)

# fit a negative binomial model, with more chains and control arguments
fit_nb <- fit_bycatch(Takes ~ 1,
  data = d, time = "Year",
  effort = "Sets", family = "nbinom2",
  time_varying = FALSE, iter = 2000, chains = 4,
  control = list(adapt_delta = 0.99, max_treedepth = 20)
)

# fit a time varying model
fit <- fit_bycatch(Takes ~ 1,
  data = d, time = "Year",
  effort = "Sets", family = "poisson", time_varying = TRUE
)

# include data for expansion to unobserved sets
fit_nb <- fit_bycatch(Takes ~ 1,
  data = d, time = "Year",
  effort = "Sets", family = "nbinom2",
  expansion_rate = "expansionRate",
  time_varying = FALSE, iter = 2000, chains = 4,
  control = list(adapt_delta = 0.99, max_treedepth = 20)
)

eric-ward/bycatch documentation built on July 5, 2023, 4:37 p.m.