Diagnostic plots for age / length composition data from a fitted Rceattle
model, drawn with ggplot2 for a consistent look with plot.rceattle_osa().
With the default residual_type = "pearson" three figures are produced per
fleet x composition type:
Pearson residual bubbles by year and bin, faceted by fleet (and, for joint-sex data, by sex); red = positive, blue = negative, sized by magnitude. The Pearson residual is \((p - \hat p)/\sqrt{\hat p (1 - \hat p)/N}\), the same form used by
residuals.Rceattle().Annual composition – observed (shaded area) vs fitted (line) proportion at age / length, one panel per year. Joint-sex data are mirrored (females up, males down).
Aggregated composition – the same, summed over (hindcast) years.
The shaded area and fitted line span only the observed bins (they do not
extend past the first/last bin), and bins with zero observed proportion are
retained (only NA bins are dropped), so the curves are not interpolated
across gaps.
Usage
plot_comp(
Rceattle,
file = NULL,
model_names = NULL,
species = NULL,
cex = 3,
lwd = 3,
right_adj = 0,
residual_type = c("pearson", "osa")
)Arguments
- Rceattle
A single fitted
Rceattlemodel.- file
Optional filename stem; when supplied, each figure is also saved as a PNG.
- model_names
Unused (kept for back-compatibility).
- species
Optional species code(s) to plot (matched against the
Speciescolumn);NULL(default) plots all. Mirrors thespeciesargument ofresiduals.Rceattle()andplot.rceattle_osa().- cex
Unused (kept for back-compatibility).
- lwd
Width of the fitted-composition line. Default
3.- right_adj
Unused (kept for back-compatibility).
- residual_type
"pearson"(default) for the ggplot2 Pearson-residual and composition-fit figures drawn here, or"osa"to instead draw the one-step-ahead residual diagnostics viaosa_residuals()andplot.rceattle_osa()– a Q-Q plot (with SDNR / tail annotation) alongside signed OSA- and Pearson-residual bubbles. The"osa"path builds its observation data on demand, so it works with any fit.