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Plot the prior/posterior distributions of a parameter

Source: R/plot_distribs.R
plot_distribs.Rd

Plot prior and posterior distributions implied by a specs list or fitted metabolism model.

Usage

plot_distribs(
  dist_data,
  parname = c("GPP_daily", "alpha", "Pmax", "ER_daily", "K600_daily",
    "K600_daily_meanlog", "lnK600_lnQ_intercept", "lnK600_lnQ_slope", "K600_lnQ_nodes",
    "K600_daily_sdlog", "K600_daily_sigma", "err_obs_iid_sigma", "err_proc_acor_phi",
    "err_proc_acor_sigma", "err_proc_iid_sigma", "err_mult_GPP_sdlog"),
  index = TRUE,
  style = c("dygraphs", "ggplot2")
)

Arguments

dist_data

Either a specs list (for priors only) or a metab_model object (for both priors and posteriors).

parname

Character. the name of the parameter whose distribution(s) you wish to plot.

index

Integer or logical. Applicable only if plotting posteriors, and useful only if the parname is for a parameter having multiple (e.g., daily) instances. In this case, the index selects the instance and corresponds to the row number in the data.frame element of get_fit(metab_model) that contains the parameter, e.g. get_fit(metab_model)$daily for 'GPP_daily'. The default, TRUE, selects and pools all instances of the parameter.

style

Character indicating which graphics package to use.

Value

A ggplot object when style = "ggplot2" or a dygraph object when style = "dygraphs".

Examples

if (FALSE) { # interactive()
# priors only
plot_distribs(specs('bayes', K600_daily_mu=30), 'K600_daily')

# posteriors, too
mm <- metab(specs(mm_name('bayes')), data=data_metab('1', res='30'))
plot_distribs(mm, 'GPP_daily', 1)

# with modifications
plot_distribs(mm, 'err_proc_iid_sigma') |>
  dygraphs::dyRangeSelector(dateWindow=c(-0.1,1.3)) |>
  dygraphs::dyAxis(name='y', valueRange=c(0,15))
}