Reproduces the standard influence display of the beta-regression
diagnostics literature: the per-observation conformal normal curvature
\(B_{E_t}\) (or the aggregate contribution \(m[r]_t\)) plotted against
the observation index, with the reference cutoff drawn and the most
influential observations labelled. This is the plot practitioners of local
influence expect to see; the conformal screening in clis_screen() and
plot_clis() complements it with an error-controlled declaration.
Usage
plot_influence(
object,
scheme = "caseweights",
p = 1L,
measure = c("B_Et", "m_r"),
r_plot = 3L,
use_fisher = TRUE,
penalised = FALSE,
label_top = 5L,
labels = NULL
)Arguments
- object
A fitted BEZI/BEOI
gamlssmodel.- scheme
Perturbation scheme: "caseweights" (default), "disccovar", "meancovar", or "preccovar".
- p
Covariate index for the covariate-perturbation schemes.
- measure
Which quantity to plot: "B_Et" (default) or "m_r".
- r_plot
Aggregate-contribution order when
measure = "m_r".- use_fisher
Logical; use the Fisher information (default
TRUE).- penalised
Logical; use the penalised information (default
FALSE).- label_top
Integer; number of most-influential points to label.
- labels
Optional character vector of observation labels (for example country codes); defaults to the observation index.