Visualize Model Fit with Input Data

Creates a comprehensive visualization of the model fit overlaid on the input data. The plot can include multiple visualization elements:

• Main plot showing data points and model fit with confidence intervals

• Optional zoomed-in view of the observations

• Optional secondary x-axis for alternative time scales

• Optional time window highlights

• Optional posterior distribution for the t0 parameter

Usage

plot_fit(
  x,
  CI = 0.95,
  legend_labels = NULL,
  legend_title = "group",
  zoom = TRUE,
  full_process = TRUE,
  sec_axis_breaks = NULL,
  sec_axis_labels = NULL,
  t0_posterior_color = "darkorange",
  shadows_colors = NULL
)

Arguments

x

A bipod object containing a 'fit' field with model results

CI

Numeric value between 0 and 1 specifying the confidence interval width for the fit line. For example, 0.95 shows the 95% confidence interval. Defaults to 0.95

legend_labels

Character vector providing custom labels for each group in x$counts$group. Must match the number of unique groups. Defaults to NULL

legend_title

Character string specifying the title for the plot legend. Defaults to "group"

zoom

Logical indicating whether to include a zoomed-in panel focusing on the observation period. Defaults to TRUE

full_process

Logical indicating whether to display the posterior distribution for the t0 parameter. Defaults to TRUE

sec_axis_breaks

Numeric vector specifying the positions of breaks on the secondary x-axis. Must be provided together with sec_axis_labels. Defaults to NULL

sec_axis_labels

Character vector providing labels for the secondary x-axis breaks. Must be provided together with sec_axis_breaks. Defaults to NULL

t0_posterior_color

Character string specifying the color for the t0 posterior distribution plot. Defaults to "darkorange"

shadows_colors

Character vector specifying colors for highlighting different time windows in the plot. Defaults to NULL

Value

A ggplot2 object containing the visualization