View source: R/plot.tag.attrition.R
plot.tag.attrition | R Documentation |
Plot the observed and predicted tag recaptures against time at liberty by tagging program, or all tagging programs combined. The plot is either a time series of the difference between the observed and predicted, or a time series of the recaptures. A loess smoother is put through the differences.
plot.tag.attrition(
tagdat.list,
tagdat.names = NULL,
facet = "program",
plot.diff = TRUE,
scale.diff = TRUE,
show.legend = TRUE,
show.points = FALSE,
palette.func = default.model.colours,
save.dir,
save.name,
...
)
tagdat.list |
A list, or an individual data.frame, of tagging data created by the |
tagdat.names |
A vector of character strings naming the models for plotting purposes. If not supplied, model names will be taken from the names in the tagdat.list (if available) or generated automatically. |
facet |
What variable do you want to group by: "none" (no grouping), "program" (by tagging program - default), "region" (by recapture region). |
plot.diff |
Do you want to plot the difference between the observed and predicted, or a time series of recaptures? TRUE (default) or FALSE. |
scale.diff |
If TRUE, the difference between observed and predicted is scaled by the mean number of observed returns. |
show.legend |
Do you want to show the plot legend, TRUE (default) or FALSE. |
show.points |
Do you want to show points as well as the smoother for the difference plots? Default is FALSE. |
palette.func |
A function to determine the colours of the models. The default palette has the reference model in black. It is possible to determine your own palette function. Two functions currently exist: default.model.colours() and colourblind.model.colours(). |
save.dir |
Path to the directory where the outputs will be saved |
save.name |
Name stem for the output, useful when saving many model outputs in the same directory |
... |
Passes extra arguments to the palette function. Use the argument all.model.names to ensure consistency of model colours when plotting a subset of models. |
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