Plot a choice-based discounting model

Visualize a fitted fit_dd_choice() model. For a structural fit, type = "population" (default) draws the implied discount curve from the estimated discount rate, type = "individual" adds the per-subject curves, and type = "parameters" shows the subject-k distribution. For both structural and descriptive (Young 2018) fits, type = "calibration" plots the observed choice proportion against the fitted P(choose LL), binned by fitted probability (a likelihood-geometry-agnostic goodness-of-fit view). Descriptive fits have no structural discount rate, so the curve/parameter types are unavailable.

Usage

# S3 method for class 'beezdiscounting_choice'
plot(
  x,
  type = NULL,
  ids = NULL,
  at = NULL,
  n_points = 200,
  x_trans = c("log10", "linear"),
  show_observed = TRUE,
  ...
)

Arguments

x

A beezdiscounting_choice object.

type

One of "population", "individual", "calibration", "parameters". Defaults to "population" (structural) or "calibration" (descriptive).

ids

Optional subset of subject ids for type = "individual".

at

Optional named list conditioning the curve on factor levels / covariate values.

n_points

Number of delay points in the curve grid.

x_trans

Delay-axis scale: "log10" (default) or "linear".

show_observed

Unused for the implied discount curve (kept for a consistent signature across tiers).

...

Unused.

Value

A ggplot2::ggplot object.

Examples

# \donttest{
ch <- simulate_dd_choice(n_subjects = 12, seed = 1)
fit <- fit_dd_choice(ch, equation = "mazur")
plot(fit)

plot(fit, type = "calibration")

# }