plot_profile | R Documentation |
Plot results from MCBE parameter profile analysis
plot_profile(
sim_summary,
nm_par = "steep",
nm_obj = c("parms", "parm.cons"),
like_pattern = "^lk.",
like_groups = c("L", "D", "U", "lenc", "agec", "SR"),
like_shift = "min_par",
like_prop_exclude = c("lk.total", "lk.unwgt.data"),
par_args = list(mfrow = c(2, 1), mar = c(3, 3, 0, 0), mgp = c(1, 0.3, 0), tck = -0.01),
plot_profiles = TRUE,
plot_stacked = TRUE
)
sim_summary |
Output object from summarize_MCBE |
nm_par |
Name of parameter to plot profile |
nm_obj |
Name of object where par should be found in sim_summary. By default, plot_profile will look in parms and parm.cons and use the first instance of nm_par it finds. It works with data frames in sim_summary like parms and is programmed to work with parm.cons as a special case, but may not work with other objects within sim_summary. |
like_pattern |
pattern to use to identify likelihood components from |
like_groups |
names of groups to use when plotting grouped likelihoods. The function adds "^lk."
to the group names to find parameters to group in |
like_shift |
method to use to scale likelihood components for plotting: "min" shifts each likelihood component by the overall minimum, "min_par" shifts each likelihood component by its own minimum, "none" returns raw likelihoods |
like_prop_exclude |
Names of columns in |
par_args |
arguments to pass to |
plot_profiles |
logical. Plot likelihood profiles as lines, possibles shifted with like_shift? |
plot_stacked |
logical. Plot likelihood profiles as stacked areas ( |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.