Plot TMB Mixed-Effects Demand Model

Usage

# S3 method for class 'beezdemand_tmb'
plot(
  x,
  type = c("demand", "individual", "parameters"),
  ids = NULL,
  prices = NULL,
  show_population = TRUE,
  show_observed = TRUE,
  show_pred = NULL,
  x_trans = c("log10", "log", "linear", "pseudo_log"),
  y_trans = NULL,
  inv_fun = NULL,
  x_limits = NULL,
  y_limits = NULL,
  x_lab = NULL,
  y_lab = NULL,
  style = c("modern", "apa"),
  observed_point_alpha = 0.3,
  observed_point_size = 1.5,
  pop_line_alpha = 1,
  pop_line_size = 1.2,
  ind_line_alpha = 0.3,
  ind_line_size = 0.5,
  ...
)

Arguments

x: A beezdemand_tmb object.
type: Character. One of "demand" (population curve with data), "individual" (per-subject curves), "parameters" (parameter distributions).
ids: Character vector of subject IDs to plot (for individual type).
prices: Optional numeric vector of prices for curve generation.
show_population: Logical. Show population curve overlay.
show_observed: Logical. Show observed data points.
show_pred: Character. Which predictions to show: "population", "individual", or "both". If NULL (default), determined by type.
x_trans: Character. X-axis transformation.
y_trans: Character. Y-axis transformation. If NULL (default), uses "pseudo_log" which handles zero values gracefully.
inv_fun: Optional function to back-transform y-axis. For zben and exponential equations, the inverse link is applied automatically by default so all demand plots are on the consumption scale.
x_limits, y_limits: Numeric length-2 vectors for axis limits.
x_lab: Character. X-axis label.
y_lab: Character. Y-axis label.
style: Character. Plot style: "modern" or "apa".
observed_point_alpha, observed_point_size: Numeric. Aesthetics for observed data points.
pop_line_alpha, pop_line_size: Numeric. Aesthetics for population curve.
ind_line_alpha, ind_line_size: Numeric. Aesthetics for individual curves.
...: Additional arguments.

Value

A ggplot2 object.

Examples

# \donttest{
data(apt)
fit <- fit_demand_tmb(apt, equation = "exponential", verbose = 0)
#>   equation='exponential': Dropped 14 zero-consumption observations (146 remaining).

# Population demand curve
plot(fit, type = "demand")
#> Warning: log-10 transformation introduced infinite values.
#> Warning: log-10 transformation introduced infinite values.


# Individual curves for selected subjects
plot(fit, type = "individual", ids = c("19", "51"))
#> Warning: log-10 transformation introduced infinite values.
#> Warning: log-10 transformation introduced infinite values.
#> Warning: log-10 transformation introduced infinite values.


# Parameter distributions
plot(fit, type = "parameters")

# }