Produce marginal GoF plot
marginal_gof_copula(
marginal,
observed,
name,
type,
treat,
return_data = FALSE,
grid = NULL,
...
)Estimated marginal distribution represented by a list with three elements in the following order: the estimated cdf, pdf, and inverse cdf.
Observed values. These are used for the histogram.
Name of the endpoint (used in the plot title).
Type of endpoint: "ordinal" or "continuous"
Value for the treatment indicator.
(boolean) Return the data used in the goodness-of-fit plot
(without the plot itself). This is useful when the user wants to customize the
plots, e.g., using ggplot2. See Details.
(numeric) vector of values for the endpoint at which the model-based density is computed.
Extra arguments passed onto plot() or hist() for an ordinal
and continuous endpoint, respectively.
If return_data is TRUE, this function will return a data frame that can be
used to create customized plots. The following variables are present in the
returned data frame:
observed: The empirical proportions (type = "ordinal"). NA for
type = "continuous".
upper_ci, lower_ci: Upper limit of the 95% confidence interval for the empirical
proportions. Defaults to NA if type = "continuous".
value: Value for the continuous or ordinal variable.
model_based: Estimated model-based density (type = "continuous") or
proportions (type = "ordinal")
plot.vine_copula_fit()