plot_cv plots projected bycatch estimation CVs vs observer
coverage, and returns minimum observer coverage needed to achieve
user-specified target CV and percentile.
plot_cv(te, bpue, d = 2, targetcv = 0.3, showplot = TRUE,
silent = FALSE, ...)an integer greater than 1. Total effort in fishery (e.g., trips or sets).
a positive number. Bycatch per unit effort.
a number greater than or equal to 1. Dispersion index. The dispersion
index corresponds to the variance-to-mean ratio of effort-unit-level bycatch,
so d = 1 corresponds to Poisson-distributed bycatch, and d > 1
to overdispersed bycatch.
a non-negative number less than 1. Target CV (as a proportion). If set to 0, no corresponding minimum observer coverage will be highlighted or returned.
logical. If FALSE, plotting is suppressed.
logical. If TRUE, print output to terminal is suppressed.
additional arguments for compatibility with Shiny.
If targetcv is non-zero, a list with one component:
minimum observer coverage in terms of percentage.
Returned invisibly.
Caveat: plot_cv assumes that (1) observer coverage is
representative, (2) bycatch (bpue) is in terms of individuals (not
weight) per unit effort, and (3) the specified dispersion index reflects
the highest level of any hierarchical variance (e.g., using dispersion index
at trip level if greater than that at set level). Violating these assumptions
will likely result in negatively biased projections of the observer coverage
needed to meet a specified objective. More conservative (higher) projections
can be obtained by using a higher dispersion index d. Users may want
to explore uncertainty in dispersion index and in bycatch per unit effort by
varying those inputs.