Skip to contents

Plot Serial Interval Fit from si_estim Result

Source: R/plot_si_fit.R
plot_si_fit_result.Rd

A convenience wrapper for plot_si_fit that accepts the output from si_estim directly, automatically handling the weight aggregation for different distribution types and number of routes.

Usage

plot_si_fit_result(
  si_result,
  dat,
  dist = c("normal", "gamma"),
  scaling_factor = 1
)

Arguments

si_result

list; the output from si_estim containing mean, sd, wts, and n_routes components.

dat

numeric vector; the index case-to-case (ICC) intervals in days.

dist

character; the distribution family. Must be either "normal" (default) or "gamma". Should match the distribution used in si_estim().

scaling_factor

numeric; multiplicative factor to adjust the height of the fitted density curve. Defaults to 1.

Value

A ggplot2 object.

Details

This function reads n_routes directly from the si_result object and aggregates component weights automatically:

  • For normal distribution: the Co-primary weight is taken directly, and weights for routes 2 to n_routes are aggregated by summing the two symmetric components (positive and negative).

  • For gamma distribution: weights are taken directly as the first n_routes - 1 values from si_result$wts.

See also

si_estim, plot_si_fit

Examples

set.seed(123)
icc_data <- c(
  abs(rnorm(15, mean = 0, sd = 2)),
  rnorm(40, mean = 12, sd = 3),
  rnorm(15, mean = 24, sd = 4)
)
icc_data <- round(pmax(icc_data, 0))

# \donttest{
# 4 routes (default)
result <- si_estim(icc_data, n = 50)
plot_si_fit_result(result, icc_data, dist = "normal")


# 5 routes
result5 <- si_estim(icc_data, n = 50, n_routes = 5)
plot_si_fit_result(result5, icc_data, dist = "normal")

# }